Farming Assistance Web Service

Data mining, Networking, Parallel And Distributed System, Web Application
Name Farming Assistance Web Service Technology DotNET,MS SQL Category Web Application Description A Web project to help farmers ensure greater profitability through direct farmer to supplier and farmer to farmer communication. This service boosts business communication and brings transparency in the system. This innovative site allows for good farmer, retailer and supplier communication. It allows farmers to login and communicate to respective dealers. When dealers publish an advertisement or offer, the respective farmers get notified via Sms message. The farmers may also submit their greviences and complaints to respective dealers or authorities using their farmer login on a separate complaints page and authorities will get acess to that page regularly using their login id and passwords. IEEE Paper Yes IEEE Paper Year 2015
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Smart Health Consulting Project

Data mining, Networking, Web Application
Name Smart Health Consulting Project Technology DotNET,MS SQL Category Web Application Description This system aims at maintaining patient health records and even getting appointments from various doctors for related treatments. The system user must register as a member of this system and keep updating his medical history. Patients can then select from a list of specialized doctors for respective treatments such as (skin specialist, ENT specialist cardiologist etc) at particular locations. Patients may also select suitable appointment timings for their meeting. This Project contains 7 useful areas: i. General User area ii. Doctor’s area iii. Patient’s area iv. Transaction/Blling area v. Administrator area vi. Pharmacy area vii. Insurance area IEEE Paper Yes IEEE Paper Year 2015
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Artificial Intelligence Dietician

Data mining, Parallel And Distributed System, Web Application
Name Artificial Intelligence Dietician Technology DotNET,MS SQL Category Web Application Description The online artificial dietician is a bot with artificial intelligence about human diets. It acts as a diet consultant similar to a real dietician. Dieticians are educated with nutrient value of foods. A dietician consults a person based on his schedule, body type, height and weight. The system too asks all this data from the user and processes it. It asks about how many hour the user works, his height, weight, age etc. The system stores and processes this data and then calculates the nutrient value needed to fill up users needs. The system then shows an appropriate diet to the users and asks if user is ok with it, else it shows other alternate diets to fill up…
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Customer Behaviour Prediction Using Web Usage Mining

Cloud Computing, Data mining, Networking, Parallel And Distributed System, Web Application
Name Customer Behaviour Prediction Using Web Usage Mining Technology DotNET,MS SQL Category Web Application Description Web usage mining involves first recording behavior and flow of customers on a website and then mining through this data for behavioural patterns. It is an important part of ecommerce world that allows websites to go through previously recorded web traffic data. Ecommerce sites analyse this data in order to provide better performance and also suggest better products and services to customers by identifying them next time. The system is tuned to record web shopping/buying patterns and track various analytics data that tend to provide future prediction statistics. The system scans for user budget tracking, tallying to previous years, user bounce rates- number of users returning from payment page and other site usage factors. Factors…
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Web Mining For Suspicious Keyword Prominence

Cloud Computing, Data mining, Web Application
Name Web Mining For Suspicious Keyword Prominence Technology DotNET,MS SQL Category Web Application Description Web mining can be termed as an information mining method to naturally search, collect and organize data from indexed online records which might be in various organized, unstructured or semi-organized structure. We usually use web mining techniques in order to assess the viability of a specific web page/entity in order to figure out various factors related to it. This project consolidates the best researched mechanisms from the semantic web and synaptic web at low entropy in order to build structural engineering of Semantic-Synaptic web mining. Our proposed project aims at web mining for finding out density of selected keywords in order to check its keyword prominence on those web pages. This is an important factor in…
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Active Chat Monitoring and Suspicious Chat Detection over Internet

Data mining, Security & Encryption, Web Application
Name Active Chat Monitoring and Suspicious Chat Detection over Internet Technology DotNET,MS SQL Category Web Application Description A lot of terrorist activities and groups communicate over apps and chat programs over the internet. They also use these chat application over the internet for getting their message to young generation and making new terrorists. Well we here propose a internet chat application that actively monitors various chats going on and also alerts the admin about any suspicious chat process taking place. The system is built to process all chats taking place over and saving them with history. The chat process is handled by server. As data passes through server it continuously scans it for any suspicious keywords. The admin may however keep a watch at any chat he desires. A special…
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Criminal Investigation Tracker with Suspect Prediction

Data mining, Multimedia, Networking, Web Application
Name Criminal Investigation Tracker with Suspect Prediction Technology DotNET,MS SQL Category Web Application Description We here propose a criminal investigation tracker system that tracks the investigation status of criminal cases with logs and also predicts primary suspects. The system is proposed to help agencies like CBI, CID and other such bureau’s to sped up investigation process and track status of multiple cases at a time. The system keeps logs of a case which includes case summary, people involved, disputes, past criminal history of those involved, Items recovered on scene and other details. The system realizes the type of case, allows admin to update the status of investigation, upload more images of crime, items found on scene etc. This allows authorized officers to check case status and look into its status…
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Opinion Mining For Social Networking Site

Data mining, Parallel And Distributed System, Web Application
Name Opinion Mining For Social Networking Site Technology DotNET,MS SQL Category Web Application Description This system uses opinion mining methodology in order to achieve desired functionality. Opinion Mining for Social Networking Site is a web application. Here the user will post his views related to some subject other users will view this post and will comment on this post. The System takes comments of various users, based on the opinion, system will specify whether the posted topic is good, bad, or worst. User can change his own profile picture and can update his status. These changes can be viewed by various users. We use a database of sentiment based keywords along with positivity or negativity weight in database and then based on these sentiment keywords mined in user comment is…
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Web Data Mining To Detect Online Spread Of Terrorism

Cloud Computing, Data mining, Networking, Parallel And Distributed System, Web Application
Name Web Data Mining To Detect Online Spread Of Terrorism Technology DotNET,MS SQL Category Web Application Description Terrorism has grown its roots quite deep in certain parts of the world. With increasing terrorist activities it has become important to curb terrorism and stop its spread before a certain time. So as identified internet is a major source of spreading terrorism through speeches and videos. Terrorist organizations use internet to brain wash individuals and also promote terrorist activities through provocative web pages that inspire helpless people to join terrorist organizations. So here we propose an efficient web data mining system to detect such web properties and flag them automatically for human review. Data mining is a technique used to mine out patterns of useful data from large data sets and make…
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Fake Product Review Monitoring And Removal For Genuine Online Product Reviews Using Opinion Mining

Data mining, Multimedia, Networking, Security & Encryption, Web Application
Name Fake Product Review Monitoring And Removal For Genuine Online Product Reviews Using Opinion Mining Technology DotNET,MS SQL Category Web Application Description As most of the people require review about a product before spending their money on the product. So people come across various reviews in the website but these reviews are genuine or fake is not identified by the user. In some review websites some good reviews are added by the product company people itself in order to make in order to produce false positive product reviews. They give good reviews for many different products manufactured by their own firm. User will not be able to find out whether the review is genuine or fake. To find out fake review in the website this “Fake Product Review Monitoring and…
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Monitoring Suspicious Discussions On Online Forums Using Data Mining

Data mining, Networking, Security & Encryption, Web Application
Name Monitoring Suspicious Discussions On Online Forums Using Data Mining Technology DotNET,MS SQL Category Web Application Description People now-a-days are very fond of using internet as a discussion medium. As internet technology had been increasing more and more, this technology led to many legal and illegal activities. It is found that much first-hand news has been discussed in Internet forums well before they are reported in traditional mass media. This communication channel provides an effective channel for illegal activities such as dissemination of copyrighted movies, threatening messages and online gambling etc. The law enforcement agencies are looking for solutions to monitor these discussion forums for possible criminal activities and download suspected postings as evidence for investigation. We propose a system which will tackle this problem effectively. In this project we…
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Movie Success Prediction Using Data Mining

Data mining, Multimedia, Networking, Web Application
Name Movie Success Prediction Using Data Mining Technology DotNET,MS SQL Category Web Application Description In this system we have developed a mathematical model for predicting the success class such as flop, hit, super hit of the movies. For doing this we have to develop a methodology in which the historical data of each component such as actor, actress, director, music that influences the success or failure of a movie is given is due to weight age and then based on multiple thresholds calculated on the basis of descriptive statistics of dataset of each component it is given class flop, hit, super hit label. Admin will add the film crew data. Admin will add movies data of a particular film crew. Admin will add new movie data along with film crew…
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Opinion Mining For Comment Sentiment Analysis

Cloud Computing, Data mining, Networking, Web Application
Name Opinion Mining For Comment Sentiment Analysis Technology DotNET,MS SQL Category Web Application Description Here we propose an advanced Comment Sentiment Analysis system that detects hidden sentiments in comments and rates the post accordingly. The system uses opinion mining methodology in order to achieve desired functionality. Opinion Mining for Comment Sentiment Analysis is a web application which gives review of the topic that is posted by the user. The System takes comments of various users, based on the opinion, system will specify whether the posted topic is good, bad, or worst. We use a database of sentiment based keywords along with positivity or negativity weight in database and then based on these sentiment keywords mined in user comment is ranked. Once the user logins to the system, user can view…
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Opinion Mining For Restaurant Reviews

Data mining, Networking, Parallel And Distributed System, Web Application
Name Opinion Mining For Restaurant Reviews Technology DotNET,MS SQL Category Web Application Description Here we propose an advanced Restaurant Review system that detects hidden sentiments in feedback of the customer and rates the restaurant accordingly. The system uses opinion mining methodology in order to achieve desired functionality. Opinion Mining for Restaurant Reviews is a web application which gives review of the feedback that is posted. The System takes feedback of various users, based on the opinion, system will specify whether the posted restaurant is good, bad, or worst. We use a database of sentiment based keywords along with positivity or negativity weight in database and then based on these sentiment keywords mined in user feedback is ranked. Once the user login to the system he views the restaurant and gives…
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Weather Forecasting Using Data Mining

Cloud Computing, Data mining, Multimedia, Networking, Web Application
Name Weather Forecasting Using Data Mining Technology DotNET,MS SQL Category Web Application Description Weather forecasting is the application of science and technology to predict the state of the atmosphere for a given location. Ancient weather forecasting methods usually relied on observed patterns of events, also termed pattern recognition. For example, it might be observed that if the sunset was particularly red, the following day often brought fair weather. However, not all of these predictions prove reliable. Here this system will predict weather based on parameters such as temperature, humidity and wind. This system is a web application with effective graphical user interface. User will login to the system using his user ID and password. User will enter current temperature; humidity and wind, System will take this parameter and will predict…
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E Commerce Product Rating Based On Customer Review Mining

Data mining, Networking, Parallel And Distributed System, Web Application
Name E Commerce Product Rating Based On Customer Review Mining Technology DotNET,MS SQL Category Web Application Description There are many users who purchase products through E-commerce websites. Through online shopping many E-commerce enterprises were unable to know whether the customers are satisfied by the services provided by the firm. This boosts us to develop a system where various customers give reviews about the product and online shopping services, which in turn help the E-commerce enterprises and manufacturers to get customer opinion to improve service and merchandise through mining customer reviews. An algorithm could be used to track and manage customer reviews, through mining topics and sentiment orientation from online customer reviews. In this system user will view various products and can purchase products online. Customer gives review about the merchandise…
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Sentiment Analysis for Product Rating

Cloud Computing, Data mining, Networking, Parallel And Distributed System, Web Application
Name Sentiment Analysis for Product Rating Technology DotNET,MS SQL Category Web Application Description Here we propose an advanced Sentiment Analysis for Product Rating system that detects hidden sentiments in comments and rates the product accordingly. The system uses sentiment analysis methodology in order to achieve desired functionality. This project is an E-Commerce web application where the registered user will view the product and product features and will comment about the product. System will analyze the comments of various users and will rank product. We use a database of sentiment based keywords along with positivity or negativity weight in database and then based on these sentiment keywords mined in user comment is ranked. Comment will be analyzed by comparing the comment with the keywords stored in database. The System takes comments…
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Detecting E Banking Phishing Websites Using Associative Classification

Data mining, Multimedia, Networking, Security & Encryption, Web Application
Name Detecting E Banking Phishing Websites Using Associative Classification Technology DotNET,MS SQL Category Web Application Description There are number of users who purchase products online and make payment through e- banking. There are e- banking websites who ask user to provide sensitive data such as username, password or credit card details etc often for malicious reasons. This type of e-banking websites is known as phishing website. In order to detect and predict e-banking phishing website. We proposed an intelligent, flexible and effective system that is based on using classification Data mining algorithm. We implemented classification algorithm and techniques to extract the phishing data sets criteria to classify their legitimacy. The e-banking phishing website can be detected based on some important characteristics like URL and Domain Identity, and security and encryption…
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Content Summary Generation Using NLP

Data mining, Parallel And Distributed System, Web Application
Name Content Summary Generation Using NLP Technology DotNET,MS SQL Category Web Application Description To find prominent summarized points in a collection of documents. We here propose a system to detect summarized points from a huge or multiple paragraph. We use an efficient method to discover summarized points from the provided content using Natural language processing (NLP). The provided content is divided into two parts as Summarized Content and Summarized Point. One would expect particular words to appear in the content more or less frequently: “dog” and “bone” will appear more often in documents about dogs, “cat” and “meow” will appear in documents about cats, and “the” and “is” will appear equally in both. A document typically concerns multiple topics in different proportions; thus, in a document that is 10% about…
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Product Review Analysis For Genuine Rating

Data mining, Networking, Web Application
Name Product Review Analysis For Genuine Rating Technology DotNET,MS SQL Category Web Application Description Here we propose an advanced Products Review analysis system which provides a platform to registered users to rate a particular or multiple products using this system. The system uses product review analysis in order to achieve desired functionality. Product review analysis is a web application which consist multiple products added by admin to review to rate and review them. The System takes reviews of various users, based on their personal opinion, system will specify whether the posted product is good, bad, or worst. We use a database of sentiment based keywords along with positivity or negativity weight in database and then based on these sentiment keywords mined in user review is ranked. Once the user login…
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Smart Health Prediction Using Data Mining

Data mining, Multimedia, Networking, Parallel And Distributed System, Web Application
Name Smart Health Prediction Using Data Mining Technology DotNET,MS SQL Category Web Application Description It might have happened so many times that you or someone yours need doctors help immediately, but they are not available due to some reason. The Health Prediction system is an end user support and online consultation project. Here we propose a system that allows users to get instant guidance on their health issues through an intelligent health care system online. The system is fed with various symptoms and the disease/illness associated with those systems. The system allows user to share their symptoms and issues. It then processes users symptoms to check for various illness that could be associated with it. Here we use some intelligent data mining techniques to guess the most accurate illness that…
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Student Grade Prediction Using C4.5 Decision Tree

Data mining, Multimedia, Networking, Web Application
Name Student Grade Prediction Using C4.5 Decision Tree Technology DotNET,MS SQL Category Web Application Description We here come up with a system where student final grade is predicted based on the marks he had scored during his previous course and years. In order to predict the grade of the student we need some data to analyze and to predict the grade. So we will input student basic information and their previous academic information into the system which will be used to predict the grade of the student. We here used an effective data mining algorithm to predict the result. We used C4.5 decision tree algorithm to predict the grade of the student.C4.5 is a program for inducing classification rules in the form of decision trees from a set of given…
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Online user Behavior Analysis On Graphical Model

Data mining, Parallel And Distributed System, Web Application
Name Online user Behavior Analysis On Graphical Model Technology DotNET,MS SQL Category Web Application Description Online shopping is growing on large scale. People purchase their products via internet. They just have to choose their products and make the payment. Users get their products on doorstep. Online shopping had made people’s life easier and faster. As online shopping is increasing, large amount of data on people’s online activities have become available on web. Use of such data can benefit a lot of applications. User behavior, online customer classification can be extracted from these web data. We proposed a system where we can extract the user’s online shopping behavior. System will extract user’s online behavior pattern and will show in graphical format. This graphical format helps the admin during decision making process.…
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Detecting Phishing Websites Using Machine Learning

Cloud Computing, Data mining, Parallel And Distributed System, Security & Encryption, Web Application
Name Detecting Phishing Websites Using Machine Learning Technology DotNET,MS SQL Category Web Application Description There are number of users who purchase products online and make payment through various websites.There are multiple websites who ask user to provide sensitive data such as username, password or credit card details etc. often for malicious reasons. This type of websites is known as phishing website. In order to detect and predict phishing website, we proposed an intelligent, flexible and effective system that is based on using classification Data mining algorithm. We implemented classification algorithm and techniques to extract the phishing data sets criteria to classify their legitimacy. The phishing website can be detected based on some important characteristics like URL and Domain Identity, and security and encryption criteria in the final phishing detection rate.…
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E Authentication System Using QR Code & OTP

Cloud Computing, Data mining, Networking, Parallel And Distributed System, Security & Encryption, Web Application
Name E Authentication System Using QR Code & OTP Technology DotNET,MS SQL Category Web Application Description In the proposed scheme, the user can easily and efficiently login into the system. We analyze the security and usability of the proposed scheme, and show the resistance of the proposed scheme to hacking of login credentials, shoulder surfing and accidental login. The shoulder surfing attack can be performed by the adversary to obtain the user’s password by watching over the user’s shoulder as he enters his password. Since, we have come up with a secure system schemes with different degrees of resistance to shoulder surfing have been proposed. In order to use this authentication system, user need to first register himself into this system by filing up the basic registration details. After a…
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Sentiment Based Movie Rating System

Data mining, Networking, Web Application
Name Sentiment Based Movie Rating System Technology MsSql, Dot NET Category Web Application Description We usually come across movie rating websites where users are allowed to rate ad comment on movies online. These ratings are provided as input to the website rating system. The admin then checks reviews, critic’s ratings and displays an online rating for every movie. Here we propose an online system that automatically allows users to post reviews and stores them to rate movies based on user sentiments. The system now analyzes this data to check for user sentiments associated with each comment. Our system consists of a sentiment library designed for English as well as hindi sentiment analysis. The system breaks user comments to check for sentimental keywords and predicts user sentiment associated with it. Once…
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College Enquiry Chat Bot

Data mining, Multimedia, Parallel And Distributed System, Web Application
Name College Enquiry Chat Bot Technology MsSql, Dot NET Category Web Application Description The College bot project is built using artificial algorithms that analyses user’s queries and understand user’s message. This System is a web application which provides answer to the query of the student. Students just have to query through the bot which is used for chating. Students can chat using any format there is no specific format the user has to follow. The System uses built in artificial intelligence to answer the query. The answers are appropriate what the user queries. The User can query any college related activities through the system. The user does not have to personally go to the college for enquiry. The System analyses the question and than answers to the user. The system…
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Heart Disease Prediction Project

Data mining, Multimedia, Web Application
Name Heart Disease Prediction Project Technology MsSql, Dot NET Category Web Application Description It might have happened so many times that you or someone yours need doctors help immediately, but they are not available due to some reason. The Heart Disease Prediction application is an end user support and online consultation project. Here, we propose a web application that allows users to get instant guidance on their heart disease through an intelligent system online. The application is fed with various details and the heart disease associated with those details. The application allows user to share their heart related issues. It then processes user specific details to check for various illness that could be associated with it. Here we use some intelligent data mining techniques to guess the most accurate illness…
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Topic Detection Using Keyword Clustering

Data mining, Networking, Parallel And Distributed System, Web Application
Name Topic Detection Using Keyword Clustering Technology MsSql, Dot NET Category Web Application Description To find prominent topic in a collection of documents. We here propose a system to detect topic from a collection of document. We use an efficient method to discover topic in a collection of documents known as topic model. A topic model is a type of statistical model for discovering topics from collection of documents. One would expect particular words to appear in the document more or less frequently: “dog” and “bone” will appear more often in documents about dogs, “cat” and “meow” will appear in documents about cats, and “the” and “is” will appear equally in both. A document typically concerns multiple topics in different proportions; thus, in a document that is 10% about cats…
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Using Data Mining To Improve Consumer Retailer Connectivity

Data mining, Web Application
Name Using Data Mining To Improve Consumer Retailer Connectivity Technology MsSql, Dot NET Category Web Application Description Many consumers prefer online shopping. Day-to-day busy schedule made many consumers to visit online e-commerce websites for shopping. This saves time and cost of the consumer. With the growth of the e-commerce websites retailers tend to fail to attract more and more consumers. Consumers no longer feel difference between e-shopping and offline shopping. We proposed a system of connecting the consumer and the retailer. This system creates a bridge between consumer and retailer. We had implemented an effective data mining algorithm to analyze new patterns and trends. This system will gather data from the customer behavior pattern and is supplied to the retailers, so that retailers will able to know the new patterns…
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Symptom Based Clinical Document Clustering by Matrix Factorization

Data mining, Web Application
Name Symptom Based Clinical Document Clustering by Matrix Factorization Technology MsSql, Dot NET Category Web Application Description Here we proposed a Doctor’s clinic management kind of system, where patients will visit the clinic and if the patient is new to clinic, then receptionist will feed his/her details into the system else if the patient is already registered then the receptionist will search for the patient’s name and add into the queue. When the patients turn appear, doctor will be able to see his/her details and also can check details about previous conditions if any. After doctor sees the patient, he will make entry of medicines patient needs to take. Receptionist will get those details, and there will be a section to add symptom. So at the end we will have…
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Cancer Prediction Using Data Mining

Data mining, Web Application
Name Cancer Prediction Using Data Mining Technology MsSql, Dot NET Category Web Application Description It might have happened so many times that you or someone yours need doctors help immediately, but they are not available due to some reason. The Cancer Disease Prediction application is an end user support and online consultation project. Here, we propose a web application that allows users to get instant guidance on their cancer disease through an intelligent system online. The application is fed with various details and the cancer disease associated with those details. The application allows user to share their health related issues for cancer prediction. It then processes user specific details to check for various illness that could be associated with it. Here we use some intelligent data mining techniques to guess…
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TV Show Popularity Analysis Using Data Mining

Data mining, Web Application
Name TV Show Popularity Analysis Using Data Mining Technology MsSql, Dot NET Category Web Application Description Reality TV is the new mantra of television producers and channel executives. It is the means to increase TRP ratings and the end is always to outdo the other channels and the “similar -but-tweaked-here-and-there” shows churned out by the competition. Most of the television shows which are being telecast nowadays are reality shows specializing in dancing, singing, and acting. We conclude to build such a system that will recognize people’s sentimental comments on TV shows. The comments from the viewer will be extracted along with the viewer details such as gender, location, etc…The comments will be gathered from various sources and the entry will be maintained into the excel sheet. The excel file will…
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Detecting Fraud Apps Using Sentiment Analysis

Data mining, Networking, Web Application
Name Detecting Fraud Apps Using Sentiment Analysis Technology MsSql, Dot NET Category Web Application Description Most of us use android and IOS Mobiles these days and also uses the play store or app store capability normally. Both the stores provide great number of application but unluckily few of those applications are fraud. Such applications dose damage to phone and also may be data thefts. Hence, such applications must be marked, so that they will be identifiable for store users. So we are proposing a web application which will process the information, comments and the review of the application. So it will be easier to decide which application is fraud or not. Multiple application can be processed at a time with the web application. Also User cannot always get correct or…
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Smart Health Prediction Using Data Mining php

Data mining, Web Application
Name Smart Health Prediction Using Data Mining Technology PHP,MySql Category Web Application Description The Health Prediction system is an end user support and online consultation project. This system allows users to get instant guidance on their health issues through an intelligent health care system online. The system contains data of various symptoms and the disease/illness associated with those symptoms. It also has an option for users of sharing their symptoms and issues. The system processes those symptoms to check for various illnesses that can be associated with it. The system is designed to use intelligent data mining techniques to guess the most accurate illness based on patient’s symptoms. If user’s symptoms do not exactly match any disease in the database, then it is shows the diseases user could probably have…
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Opinion Mining For Restaurant Reviews

Data mining, Web Application
Name Opinion Mining For Restaurant Reviews Technology PHP,MySql Category Web Application Description This system rates any particular restaurant by detecting hidden sentiments in the feedback received by its customers. The system uses opinion-mining methodology in order to achieve desired functionality. Opinion Mining for Restaurant Reviews is a web application, which takes feedback of various users, and based on the opinion, system will specify whether the posted restaurant is good, bad, or worst. Database of the system have various keywords denoted as negative and positive words, which helps the system to recognize and match the feedback and rank them accordingly. The role of the admin is to post new restaurant and adds keywords in database. This application acts as a boon for food lovers and works as a source advertisements because…
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E Commerce Product Rating Based On Customer Review Mining

Data mining, Web Application
Name E Commerce Product Rating Based On Customer Review Mining Technology PHP,MySql Category Web Application Description Many users purchase products through E-commerce websites. Because of online shopping, E-commerce enterprises were unable to trace customer satisfaction for the services provided by the firm. This gave rise to an idea of a system where various customers give reviews about the product and online shopping services, which in turn help the E-commerce enterprises and manufacturers to get customer opinion to improve service and merchandise through mining customer reviews. System uses an algorithm to track and manage customer reviews, through mining topics and sentiment orientation from online customer reviews. In this system user will view and purchase products online. In addition, the Customer will give a review about the merchandise and online shopping services.…
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Crime Rate Prediction Using K Means

Data mining, Web Application
Name Crime Rate Prediction Using K Means Technology PHP,MySql Category Web Application Description Crime rate is increasing now-a-days in many countries. In today’s world with such higher crime rate and brutal crime happening, there must be some protection against this crime. Here we introduced a system by which crime rate can be reduced. Crime data must be fed into the system. We introduced data mining algorithm to predict crime. K-means algorithm plays an important role in analyzing and predicting crimes. K-means algorithm will cluster co-offenders, collaboration and dissolution of organized crime groups, identifying various relevant crime patterns, hidden links, link prediction and statistical analysis of crime data. This system will prevent crime occurring in society. Crime data is analyzed which is stored in the database. Data mining algorithm will extract…
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Document Sentiment Analysis Using Opinion Mining

Data mining, Web Application
Name Document Sentiment Analysis Using Opinion Mining Technology PHP,MySql Category Web Application Description Sentiment analysis (also known as opinion mining) refers to the use of natural language processing, text analysis to identify and extract subjective information in source materials. Sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. This system breaks user comments to check for sentimental keywords and predicts user sentiment associated with it. Once the keywords are found, the comments are with a sentiment rank. This system also scans documents in order to analyse the sentiment of the user. IEEE Paper Yes IEEE Paper Year 2015
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Evaluation of Academic Performance of Students with Fuzzy Logic

Data mining, Web Application
Name Evaluation of Academic Performance of Students with Fuzzy Logic Technology PHP,MySql Category Web Application Description Students’ academic success is evaluated by their performance in exams conducted by the institutes or Universities. This system evaluate students academic performance with fuzzy logic based performance evaluation method. In this method, we consider three parameters attendance, internal marks and external marks which are considered to evaluate students final academic performance. The fuzzy inference system has also been used to obtain Performance of Students for different input values student attendance, marks. IEEE Paper Yes IEEE Paper Year 2015
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Detecting E Banking Phishing Using Associative Classification

Data mining, Web Application
Name Detecting E Banking Phishing Using Associative Classification Technology PHP,MySql Category Web Application Description There are number of users who purchase products online and make payment through e- banking. There are e- banking websites who ask user to provide sensitive data such as username, password or credit card details etc often for malicious reasons. This type of e-banking websites is known as phishing website. In order to detect and predict e-banking phishing website. We proposed an intelligent, flexible and effective system that is based on using classification Data mining algorithm. We implemented classification algorithm and techniques to extract the phishing data sets criteria to classify their legitimacy. The e-banking phishing website can be detected based on some important characteristics like URL and Domain Identity, and security and encryption criteria in…
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Movie Success Prediction Using Data Mining PHP

Data mining, Web Application
Name Movie Success Prediction Using Data Mining PHP Technology PHP,MySql Category Web Application Description In this system we have developed a mathematical model for predicting the success class such as flop, hit, super hit of the movies. For doing this we have to develop a methodology in which the historical data of each component such as actor, actress, director, music that influences the success or failure of a movie is given is due to weight age and then based on multiple thresholds calculated on the basis of descriptive statistics of dataset of each component it is given class flop, hit, super hit label. Admin will add the film crew data. Admin will add movies data of a particular film crew. Admin will add new movie data along with film crew…
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Online Book Recommendation Using Collaborative Filtering

Data mining, Web Application
Name Online Book Recommendation Using Collaborative Filtering Technology PHP,MySql Category Web Application Description This Online book selling websites helps to buy the books online with Recommendation system which is one of the stronger tools to increase profit and retaining buyer. The book recommendation system must recommend books that are of buyer’s interest. Recommendation systems are widely used to recommend products to the end users that are most appropriate. This system uses features of collaborative filtering to produce efficient and effective recommendations. Collaborative recommendation is probably the most familiar, most widely implemented and most mature of the technologies. Collaborative recommender systems aggregate ratings of objects, recognize commonalities between users on the basis of their ratings, and generate new recommendations. IEEE Paper Yes IEEE Paper Year 2015
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Predicting User Behavior Through Sessions Web Mining

Data mining, Web Application
Name Predicting User Behavior Through Sessions Web Mining Technology PHP,MySql Category Web Application Description It is the method to extract the user sessions from the created session file. And depending on the sessions created the user behaviour is predicted by displaying them most visited page or the product. Usability is defined as the satisfaction, efficiency and effectiveness with which specific users can complete specific tasks in a particular environment. This process includes 3 stages, namely Data cleaning, User identification, Session identification. In this paper, we are implementing these three phases. Depending upon the frequency of users visiting each page mining is performed. By finding the session of the user we can analyze the user behaviour by the time spend on a particular page. IEEE Paper Yes IEEE Paper Year 2015
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Secure E Learning Using Data Mining Techniques

Data mining, Web Application
Name Secure E Learning Using Data Mining Techniques Technology PHP,MySql Category Web Application Description In today’s lifestyle every task has been executed by help of internet. The online system or the internet facilities getting more popular as well as its becoming part of human lifestyle. Now in days every individual recommends that learning should at any-place and any-time, and this recommendation is resolved by E-Learning system. Secure E-learning has been divided into two parts Data Security and user flexibility. E-learning has huge database which carries lots of student records, course records, course materials and so on. In this system user security provided by the admin, admin himself authorize to candidate to enter into the system. Course material also has been secured by using file encryption and decryption technique so that…
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Smart Health Prediction Using Data Mining

Data mining, Web Application
Name Smart Health Prediction Using Data Mining Technology PHP, MySql Category Web Application Description The Health Prediction system is an end user support and online consultation project. This system allows users to get instant guidance on their health issues through an intelligent health care system online. The system contains data of various symptoms and the disease/illness associated with those symptoms. It also has an option for users of sharing their symptoms and issues. The system processes those symptoms to check for various illnesses that can be associated with it. The system is designed to use intelligent data mining techniques to guess the most accurate illness based on patient’s symptoms. If user’s symptoms do not exactly match any disease in the database, then it is shows the diseases user could probably…
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Secure Mining of Association Rules in Horizontally Distributed Databases

Data mining
Name Secure Mining of Association Rules in Horizontally Distributed Databases Technology Dot net, MS SQL Category Data Mining Description We propose a protocol for secure mining of association rules in horizontally distributed databases. The current leading protocol is that of Kantarcioglu and Clifton [18]. Our protocol, like theirs, is based on the Fast Distributed Mining (FDM) algorithm of Cheung et al. [8], which is an unsecured distributed version of the Apriori algorithm. The main ingredients in our protocol are two novel secure multi-party algorithms—one that computes the union of private subsets that each of the interacting players hold, and another that tests the inclusion of an element held by one player in a subset held by another. Our protocol offers enhanced privacy with respect to the protocol in [18]. In…
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Policy-by-Example for Online Social Networks.

Cloud Computing, Data mining
Name Policy-by-Example for Online Social Networks. Technology Dot net, MS SQL Category Networking,Cloud Computing Description We introduce two approaches for improving privacy policy management in online social networks. First, we introduce a mechanism using proven clustering techniques that assists users in grouping their friends for group based policy management approaches. Second, we introduce a policy management approach that leverages a user's memory and opinion of their friends to set policies for other similar friends. We refer to this new approach as Same-As Policy Management. To demonstrate the e ectiveness of our policy management improvements, we implemented a prototype Facebook application and conducted an extensive user study. Leveraging proven clustering techniques, we demonstrated a 23% reduction in friend grouping time. In addition, we demonstratedconsiderable reductions in policy authoring time using Same As…
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Web Usage Mining Using Improved Frequent Pattern Tree Algorithms

Cloud Computing, Data mining
Name Web Usage Mining Using Improved Frequent Pattern Tree Algorithms Technology Dot net, MS SQL Category Data Mining,Cloud Computing Description Web mining can be broadly defined as discovery and analysis of useful information from the World Wide Web. Web Usage Mining can be described as the discovery and analysis of user accessibility pattern, during the mining of log files and associated data from a particular Web site, in order to realize and better serve the needs of Web-based applications. Web usage mining itself can be categorised further depending on the kind of usage data considered they are web server, application server and application level data. This Research work focuses on web use mining and specifically keeps tabs on running across the web utilization examples of sites from the server log…
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An Efficient Certificateless Encryption for Secure Data Sharing in Public Clouds (Data Mining with cloud)

Data mining
Name An Efficient Certificateless Encryption for Secure Data Sharing in Public Clouds (Data Mining with cloud) Technology Dot net, MS SQL Category Data Mining Description We propose a mediated certificateless encryption scheme without pairing operations for securely sharing sensitive information in public clouds. Mediated certificateless public key encryption (mCL-PKE) solves the key escrow problem in identity based encryption and certificate revocation problem in public key cryptography. However, existing mCL-PKE schemes are either inefficient because of the use of expensive pairing operations or vulnerable against partial decryption attacks. In order to address the performance and security issues, in this paper, we first propose a mCL-PKE scheme without using pairing operations. We apply our mCL-PKE scheme to construct a practical solution to the problem of sharing sensitive information in public clouds. The…
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Reversible Data Hiding With Optimal Value Transfer

Cloud Computing, Data mining
Name Reversible Data Hiding With Optimal Value Transfer Technology Dot net, MS SQL Category Data Mining,Cloud Computing Description In reversible data hiding techniques, the values of host data are modified according to some particular rules and the original host content can be perfectly restored after extraction of the hidden data on receiver side. In this paper, the optimal rule of value modification under a payload -distortion criterion is found by using an iterative procedure, and a practical reversible data hiding scheme is proposed. The secret data, as well as the auxiliary information used for content recovery, are carried by the differences between the original pixel-values and the corresponding values estimated from the neighbours. Here, the estimation errors are modified according to the optimal value transfer rule. Also, the host image…
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Infrequent Weighted Itemset Mining Using Frequent Pattern Growth

Data mining
Name Infrequent Weighted Itemset Mining Using Frequent Pattern Growth Technology Dot net, MS SQL Category Data Mining Description Frequent weighted itemsets represent correlations frequently holding in data in which items may weight differently. However, in some contexts, e.g., when the need is to minimize a certain cost function, discovering rare data correlations is more interesting than mining frequent ones. This paper tackles the issue of discovering rare and weighted itemsets, i.e., the infrequent weighted itemset (IWI) mining problem. Two novel quality measures are proposed to drive the IWI mining process. Furthermore, two algorithms that perform IWI and Minimal IWI mining efficiently, driven by the proposed measures, are presented. Experimental results show efficiency and effectiveness of the proposed approach. IEEE Paper Yes IEEE Paper Year 2014
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Public auditing cloud data storage- bilinear pairing

Cloud Computing, Data mining
Name Public auditing cloud data storage- bilinear pairing. Technology Dot net, MS SQL Category Data Mining,Cloud Computing Description Cloud data security is concern for the client while using the cloud services provided by the service provider. In this paper we are analyzed various mechanisms to ensure reliable data storage using cloud services. It mainly focuses on the way of providing computing resources in form of service rather than a product and utilities are provided to users over internet. In the cloud, application and services move to centralized huge data center and services and management of this data may not be trustworthy into cloud environment the computing resources are under control of service provider and the third-party-auditor ensures the data integrity over out sourced data. Third-party-auditor not only read but also…
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Optimization of Horizontal Aggregation in SQL by Using K-Means Clustering.

Cloud Computing, Data mining
Name optimization of Horizontal Aggregation in SQL by Using K-Means Clustering. Technology Dot net, MS SQL Category Data Mining,Cloud Computing Description To analyze data efficiently, Data mining systems are widely using datasets with columns in horizontal tabular layout. Preparing a data set is more complex task in a data mining project, requires many SQL queries, joining tables and aggregating columns. Conventional RDBMS usually manage tables with vertical form. Aggregated columns in a horizontal tabular layout returns set of numbers, instead of one number per row. The system uses one parent table and different child tables, operations are then performed on the data loaded from multiple tables. PIVOT operator, offered by RDBMS is used to calculate aggregate operations. PIVOT method is much faster method and offers much scalability. Partitioning large set…
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Interpreting the Public Sentiment Variations on Twitter

Data mining
Name Interpreting the Public Sentiment Variations on Twitter Technology Dot net, MS SQL Category Data Mining Description Millions of users share their opinions on Twitter, making it a valuable platform for tracking and analyzing public sentiment. Such tracking and analysis can provide critical information for decision making in various domains. Therefore it has attracted attention in both academia and industry. Previous research mainly focused on modeling and tracking public sentiment. In this work, we move one step further to interpret sentiment variations. We observed that emerging topics (named foreground topics) within the sentiment variation periods are highly related to the genuine reasons behind the variations. Based on this observation, we propose a Latent Dirichlet Allocation (LDA) based model, Foreground and Background LDA (FB-LDA), to distill foreground topics and filter out…
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Product Aspect Ranking and Its Applications

Data mining
Name Product Aspect Ranking and Its Applications Technology Dot net, MS SQL Category Data Mining Description Numerous consumer reviews of products are now available on the Internet. Consumer reviews contain rich and valuable knowledge for both firms and users. However, the reviews are often disorganized, leading to difficulties in information navigation and knowledge acquisition. This article proposes a product aspect ranking framework, which automatically identifies the important aspects of products from online consumer reviews, aiming at improving the usability of the numerous reviews. The important product aspects are identified based on two observations: 1) the important aspects are usually commented on by a large number of consumers and 2) consumer opinions on the important aspects greatly influence their overall opinions on the product. In particular, given the consumer reviews of…
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Supporting Privacy Protection in Personalized Web Search

Data mining
Name Supporting Privacy Protection in Personalized Web Search Technology Dot net, MS SQL Category Data Mining Description Personalized web search (PWS) has demonstrated its effectiveness in improving the quality of various search services on the Internet. However, evidences show that users’ reluctance to disclose their private information during search has become a major barrier for the wide proliferation of PWS. We study privacy protection in PWS applications that model user preferences as hierarchical user profiles. We propose a PWS framework called UPS that can adaptively generalize profiles by queries while respecting user specified privacy requirements. Our runtime generalization aims at striking a balance between two predictive metrics that evaluate the utility of personalization and the privacy risk of exposing the generalized profile. We present two greedy algorithms, namely GreedyDP and…
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Keyword Query Routing

Data mining
Name Keyword Query Routing Technology Dot net, MS SQL Category Data Mining Description Keyword search is an intuitive paradigm for searching linked data sources on the web. We propose to route keywords only to relevant sources to reduce the high cost of processing keyword search queries over all sources. We propose a novel method for computing top-k routing plans based on their potentials to contain results for a given keyword query. We employ a keyword-element relationship summary that compactly represents relationships between keywords and the data elements mentioning them. A multilevel scoring mechanism is proposed for computing the relevance of routing plans based on scores at the level of keywords, data elements, element sets, and subgraphs that connect these elements. Experiments carried out using 150 publicly available sources on the…
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Set Predicates in SQL: Enabling Set- Level Comparisons for Dynamically Formed Groups

Data mining
Name Set Predicates in SQL: Enabling Set- Level Comparisons for Dynamically Formed Groups Technology Dot net, MS SQL Category Data Mining Description In data warehousing and OLAP applications, scalar level predicates in SQL become increasingly inadequate to support a class of operations that require set-level comparison semantics, i.e., comparing a group of tuples with multiple values. Currently, complex SQL queries composed by scalar-level operations are often formed to obtain even very simple set-level semantics. Such queries are not only difficult to write but also challenging for a database engine to optimize, thus can result in costly evaluation. This paper proposes to augment SQL with set predicate, to bring out otherwise obscured set-level semantics. We studied two approaches to processing set predicates—an aggregate function-based approach and a bitmap index-based approach. Moreover,…
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An Empirical Performance Evaluation of Relational Keyword Search Techniques

Data mining
Name An Empirical Performance Evaluation of Relational Keyword Search Techniques Technology Dot net, MS SQL Category Data Mining Description Extending the keyword search paradigm to relational data has been an active area of research within the database and IR community during the past decade. Many approaches have been proposed, but despite numerous publications, there remains a severe lack of standardization for the evaluation of proposed search techniques. Lack of standardization has resulted in contradictory results from different evaluations, and the numerous discrepancies muddle what advantages are proffered by different approaches. In this paper, we present the most extensive empirical performance evaluation of relational keyword search techniques to appear to date in the literature. Our results indicate that many existing search techniques do not provide acceptable performance for realistic retrieval tasks.…
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Facilitating Document Annotation Using Content and Querying Value

Data mining
Name Facilitating Document Annotation Using Content and Querying Value Technology Dot net, MS SQL Category Data Mining Description A large number of organizations today generate and share textual descriptions of their products, services, and actions. Such collections of textual data contain significant amount of structured information, which remains buried in the unstructured text. While information extraction algorithms facilitate the extraction of structured relations, they are often expensive and inaccurate, especially when operating on top of text that does not contain any instances of the targeted structured information. We present a novel alternative approach that facilitates the generation of the structured metadata by identifying documents that are likely to contain information of interest and this information is going to be subsequently useful for querying the database. Our approach relies on the idea that humans are more likely to add the necessary metadata during creation time,…
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Context-Based Diversification for Keyword Queries Over XML Data

Data mining
Name Context-Based Diversification for Keyword Queries Over XML Data Technology Dot net, MS SQL Category Data Mining Description While keyword query empowers ordinary users to search vast amount of data, the ambiguity of keyword query makes it difficult to effectively answer keyword queries, especially for short and vague keyword queries. To address this challenging problem, in this paper we propose an approach that automatically diversifies XML keyword search based on its different contexts in the XML data. Given a short and vague keyword query and XML data to be searched, we first derive keyword search candidates of the query by a simple feature selection model. And then, we design an effective XML keyword search diversification model to measure the quality of each candidate. After that, two efficient algorithms are proposed to incrementally compute top-k qualified query candidates as the diversified search intentions. Two selection criteria are…
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Customizable Pointof- Interest Queries in Road Networks

Data mining
Name Customizable Pointof- Interest Queries in Road Networks Technology Dot net, MS SQL Category Data Mining Description networks within interactive applications. We show that partition-based algorithms developed for point-topoint shortest path computations can be naturally extended to handle augmented queries such as finding the closest restaurant or the best post office to stop on the way home, always ranking POIs according to a user-defined cost function. Our solution allows different trade-offs between indexing effort (time and space) and query time. Our most flexible variant allows the road network to change frequently (to account for traffic information or personalized cost functions) and the set of POIs to be specified at query time. Even in this fully dynamic scenario, our solution is fast enough for interactive applications on continental road networks. IEEE…
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Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions

Data mining
The large number of potential applications from bridging web data with knowledge bases has led to an increase in the entity linking research. Entity linking is the task to link entity mentions in text with their corresponding entities in a knowledge base. Potential applications include information extraction, information retrieval, and knowledge base population. However, this task is challenging due to name variations and entity ambiguity. In this survey, we present a thorough overview and analysis of the main approaches to entity linking, and discuss various applications, the evaluation of entity linking systems, and future directions.
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Tweet Segmentation and Its Application to Named Entity Recognition

Data mining
Name Tweet Segmentation and Its Application to Named Entity Recognition Technology Dot net, MS SQL Category Data Mining Description Twitter has attracted millions of users to share and disseminate most up-to-date information, resulting in large volumes of data produced everyday. However, many applications in Information Retrieval (IR) and Natural Language Processing (NLP) suffer severely from the noisy and short nature of tweets. In this paper, we propose a novel framework for tweet segmentation in a batch mode, called HybridSeg . By splitting tweets into meaningful segments, the semantic or context information is well preserved and easily extracted by the downstream applications. HybridSeg finds the optimal segmentation of a tweet by maximizing the sum of the stickiness scores of its candidate segments. The stickiness score considers the probability of a segment being a phrase in English (i.e., global context) and the probability of a segment…
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Co-Extracting Opinion Targets and Opinion Words from Online Reviews Based on the Word Alignment Model

Data mining
Name Co-Extracting Opinion Targets and Opinion Words from Online Reviews Based on the Word Alignment Model Technology Dot net, MS SQL Category Data Mining Description Mining opinion targets and opinion words from online reviews are important tasks for fine-grained opinion mining, the key component of which involves detecting opinion relations among words. To this end, this paper proposes a novel approach based on the partially supervised alignment model, which regards identifying opinion relations as an alignment process. Then, a graph-based co-ranking algorithm is exploited to estimate the confidence of each candidate. Finally, candidates with higher confidence are extracted as opinion targets or opinion words. Compared to previous methods based on the nearest-neighbor rules, our model captures opinion relations more precisely, especially for long-span relations. Compared to syntaxbased methods, our word…
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Polarity Consistency Checking for Domain Independent Sentiment Dictionaries

Data mining
Polarity classification of words is important for applications such as Opinion Mining and Sentiment Analysis. A number of sentiment word/sense dictionaries have been manually or (semi)automatically constructed. We notice that these sentiment dictionaries have numerous inaccuracies. Besides obvious instances, where the same word appears with different polarities in different dictionaries, the dictionaries exhibit complex cases of polarity inconsistency, which cannot be detected by mere manual inspection. We introduce the concept of polarity consistency of words/senses in sentiment dictionaries in this paper. We show that the consistency problem is NP-complete. We reduce the polarity consistency problem to the satisfiability problem and utilize two fast SAT solvers to detect inconsistencies in a sentiment dictionary. We perform experiments on five sentiment dictionaries and WordNet to show inter- and intra-dictionaries inconsistencies.
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RRW—A Robust and Reversible Watermarking Technique for Relational Data

Data mining
Name RRW—A Robust and Reversible Watermarking Technique for Relational Data Technology Dot net, MS SQL Category Data Mining Description Advancement in information technology is playing an increasing role in the use of information systems comprising relational databases. These databases are used effectively in collaborative environments for information extraction; consequently, they are vulnerable to security threats concerning ownership rights and data tampering. Watermarking is advocated to enforce ownership rights over shared relational data and for providing a means for tackling data tampering. When ownership rights are enforced using watermarking, the underlying data undergoes certain modifications; as a result of which, the data quality gets compromised. Reversible watermarking is employed to ensure data quality along-with data recovery. However, such techniques are usually not robust against malicious attacks and do not provide any mechanism to selectively watermark a particular attribute by taking into account its role in knowledge discovery. Therefore,…
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Product Aspect Ranking and Its Applications

Cloud Computing, Data mining, Security & Encryption, Web Application
Name Product Aspect Ranking and Its Applications Technology Dot net, MS SQL Category Cloud Computing,Security,Data Mining Description Numerous consumer reviews of products are now available on the Internet. Consumer reviews contain rich and valuable knowledge for both firms and users. However, the reviews are often disorganized, leading to difficulties in information navigation and knowledge acquisition. This article proposes a product aspect ranking framework, which automatically identifies the important aspects of products from online consumer reviews, aiming at improving the usability of the numerous reviews. The important product aspects are identified based on two observations: 1) the important aspects are usually commented on by a large number of consumers and 2) consumer opinions on the important aspects greatly influence their overall opinions on the product. In particular, given the consumer reviews…
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Typicality-Based Collaborative Filtering Recommendation

Cloud Computing, Data mining, Security & Encryption
Name Typicality-Based Collaborative Filtering Recommendation Technology Dot net, MS SQL Category Cloud Computing,Security,Data Mining Description Collaborative filtering (CF) is an important and popular technology for recommender systems. However, current CF methods suffer from such problems as data sparsity, recommendation inaccuracy, and big-error in predictions. In this paper, we borrow ideas of object typicality from cognitive psychology and propose a novel typicality-based collaborative filtering recommendation method named TyCo. A distinct feature of typicality-based CF is that it finds “neighbors” of users based on user typicality degrees in user groups (instead of the corated items of users, or common users of items, as in traditional CF). To the best of our knowledge, there has been no prior work on investigating CF recommendation by combining object typicality. TyCo outperforms many CF recommendation methods…
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Panda: Public Auditing for Shared Data with Efficient User Revocation in the Cloud

Cloud Computing, Data mining, Parallel And Distributed System, Security & Encryption, Web Application
With data storage and sharing services in the cloud, users can easily modify and share data as a group. To ensure shared data integrity can be verified publicly, users in the group need to compute signatures on all the blocks in shared data. Different blocks in shared data are generally signed by different users due to data modifications performed by different users. For security reasons, once a user is revoked from the group, the blocks which were previously signed by this revoked user must be re-signed by an existing user. The straightforward method, which allows an existing user to download the corresponding part of shared data and re-sign it during user revocation, is inefficient due to the large size of shared data in the cloud. In this paper, we propose…
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Query Aware Determinization of Uncertain Objects

Data mining
This paper considers the problem of determinizing probabilistic data to enable such data to be stored in legacy systems that accept only deterministic input. Probabilistic data may be generated by automated data analysis/enrichment techniques such as entity resolution, information extraction, and speech processing. The legacy system may correspond to pre-existing web applications such as Flickr, Picasa, etc. The goal is to generate a deterministic representation of probabilistic data that optimizes the quality of the end-application built on deterministic data. We explore such a determinization problem in the context of two different data processing tasks -- triggers and selection queries. We show that approaches such as thresholding or top-1 selection traditionally used for determinization lead to suboptimal performance for such applications. Instead, we develop a query-aware strategy and show its advantages…
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Discovery of Ranking Fraud for Mobile Apps

Data mining
Ranking fraud in the mobile App market refers to fraudulent or deceptive activities which have a purpose of bumping up the Apps in the popularity list. Indeed, it becomes more and more frequent for App develops to use shady means, such as inflating their Apps’ sales or posting phony App ratings, to commit ranking fraud. While the importance of preventing ranking fraud has been widely recognized, there is limited understanding and research in this area. To this end, in this paper, we provide a holistic view of ranking fraud and propose a ranking fraud detection system for mobile Apps. Specifically, we investigate two types of evidences, ranking based evidences and rating based evidences, by modeling Apps’ ranking and rating behaviors through statistical hypotheses tests. In addition, we propose an optimization…
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A Query Formulation Language for the data web

Data mining
Name A Query Formulation Language for the data web Technology Dot net Category Data mining Description We present a query formulation language called MashQL in order to easily query and fuse structured data on the web. The main novelty of MashQL is that it allows people with limited IT-skills to explore and query one or multiple data sources without prior knowledge about the schema, structure, vocabulary, or any technical details of these sources. More importantly, to be robust and cover most cases in practice, we do not assume that a data source should have -an offline or inline- schema. This poses several language-design and performance complexities that we fundamentally tackle. To illustrate the query formulation power of MashQL, and without loss of generality, we chose the Data Web scenario. We…
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Efficient and Discovery of Patterns in Sequence Data Sets.

Data mining
Name Efficient and Discovery of Patterns in Sequence Data Sets. Technology Dot net Category Data Mining Description Existing sequence mining algorithms mostly focus on mining for subsequences. However, a large class of applications, such as biological DNA and protein motif mining, require efficient mining of “approximate” patterns that are contiguous. The few existing algorithms that can be applied to find such contiguous approximate pattern mining have drawbacks like poor scalability, lack of guarantees in finding the pattern, and difficulty in adapting to other applications. In this paper, we present a new algorithm called Flexible and Accurate Motif DEtector (FLAME). FLAME is a flexible suffix-tree-based algorithm that can be used to find frequent patterns with a variety of definitions of motif (pattern) models. It is also accurate, as it always finds…
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Mining Web Graphs for Recommendations.

Data mining
Name Mining Web Graphs for Recommendations. Technology .net Category Data Mining Description As the exponential explosion of various contents generated on the Web, Recommendation techniques have become increasingly indispensable. Innumerable different kinds of recommendations are made on the Web every day, including music, images, books recommendations, query suggestions, etc. No matter what types of data sources are used for the recommendations, essentially these data sources can be modeled in the form of graphs. In this paper, aiming at providing a general framework on mining Web graphs for recommendations, (1) we first propose a novel diffusion method which propagates similarities between different recommendations; (2) then we illustrate how to generalize different recommendation problems into our graph diffusion framework. The proposed framework can be utilized in many recommendation tasks on the World…
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Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques

Data mining
Name Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques Technology .net Category Data Mining Description Recommender systems are becoming increasingly important to individual users and businesses for providing personalized recommendations. However, while the majority of algorithms proposed in recommender systems literature have focused on improving recommendation accuracy, other important aspects of recommendation quality, such as the diversity of recommendations, have often been overlooked. In this paper, we introduce and explore a number of item ranking techniques that can generate recommendations that have substantially higher aggregate diversity across all users while maintaining comparable levels of recommendation accuracy. Comprehensive empirical evaluation consistently shows the diversity gains of the proposed techniques using several real-world rating datasets and different rating prediction algorithms. IEEE Paper Yes IEEE Paper Year 2012 Contact Form [contact-form-7 id="71" title="Contact form…
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Predicting missing items in shopping cart using fast algorithm

Data mining
Name Predicting missing items in shopping cart using fast algorithm Technology .net Category Data Mining Description ABSTRACT Prediction in shopping cart uses partial information about the contents of a shopping cart for the prediction of what else the customer is likely to buy. In order to reduce the rule mining cost, a fast algorithm generating frequent itemsets without generating candidate itemsets is proposed. The algorithm uses Boolean vector with relational AND operation to discover frequent itemsets and generate the association rule. Association rules are used to identify relationships among a set of items in database. Initially Boolean Matrix is generated by transforming the database into Boolean values. The frequent itemsets are generated from the Boolean matrix. Then association rules are to generated from the already generated frequent itemsets. The association…
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A Threshold-based Similarity Measure for Duplicate Detection

Data mining
Name A Threshold-based Similarity Measure for Duplicate Detection Technology .net Category Data Mining Description In order to extract beneficial information and recognize a particular pattern from huge data stored in different databases with different formats, data integration is essential. However the problem that arises here is that data integration may lead to duplication. In other words, due to the availability of data in different formats, there might be some records which refer to the same entity. Duplicate detection or record linkage is a technique which is used to detect and match duplicate records which are generated in data integration process. Most approaches concentrated on string similarity measures for comparing records. However, they fail to identify records which share the semantic information. So, in this study, a thresholdbased method which takes…
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Efficient Multi-dimensional Fuzzy Search for Personal Information Management Systems

Data mining
Name Efficient Multi-dimensional Fuzzy Search for Personal Information Management Systems Technology .net Category Data Mining Description With the explosion in the amount of semi-structured data users access and store in personal information management systems, there is a critical need for powerful search tools to retrieve often very heterogeneous data in a simple and efficient way. Existing tools typically support some IR-style ranking on the textual part of the query, but only consider structure (e.g., file directory) and metadata (e.g., date, file type) as filtering conditions. We propose a novel multi-dimensional search approach that allows users to perform fuzzy searches for structure and metadata conditions in addition to keyword conditions. Our techniques individually score each dimension and integrate the three dimension scores into a meaningful unified score. We also design indexes…
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Enabling Multilevel Trust in Privacy Preserving Data Mining

Data mining
Name Enabling Multilevel Trust in Privacy Preserving Data Mining Technology .net Category Data Mining Description Privacy Preserving Data Mining (PPDM) addresses the problem of developing accurate models about aggregated data without access to precise information in individual data record. A widely studied perturbation-based PPDM approach introduces random perturbation to individual values to preserve privacy before data are published. Previous solutions of this approach are limited in their tacit assumption of single-level trust on data miners. In this work, we relax this assumption and expand the scope of perturbation-based PPDM to Multilevel Trust (MLT-PPDM). In our setting, the more trusted a data miner is, the less perturbed copy of the data it can access. Under this setting, a malicious data miner may have access to differently perturbed copies of the same…
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Slicing A New Approach to Privacy Preserving Data Publishing.

Data mining, Security & Encryption
Name Slicing A New Approach to Privacy Preserving Data Publishing. Technology Java Category Security & Data Mining Description Several anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving microdata publishing. Recent work has shown that general- ization loses considerable amount of information, especially for high-dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separation between quasi- identifying attributes and sensitive attributes. IEEE Paper Yes IEEE Paper Year 2013 Contact Form [contact-form-7 id="71" title="Contact form 1"]
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Advance Mining of Temporal High Utility Itemset

Data mining
Name Advance Mining of Temporal High Utility Itemset Technology .net Category Data Mining Description The stock market domain is a dynamic and unpredictable environment. Traditional techniques, such as fundamental and technical analysis can provide investors with some tools for managing their stocks and predicting their prices. However, these techniques cannot discover all the possible relations between stocks and thus there is a need for a different approach that will provide a deeper kind of analysis. Data mining can be used extensively in the financial markets and help in stock-price forecasting. Therefore, we propose in this paper a portfolio management solution with business intelligence characteristics. We know that the temporal high utility itemsets are the itemsets with support larger than a pre-specified threshold in current time window of data stream. Discovery…
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A Framework for Personal Mobile Commerce Pattern Mining and Prediction

Data mining
Name A Framework for Personal Mobile Commerce Pattern Mining and Prediction Technology .net Category Data Mining Description In many applications, including location based services, queries may not be precise. In this paper, we study the problem of efficiently computing range aggregates in a multidimensional space when the query location is uncertain. Specifically, for a query point Q whose location is uncertain and a set S of points in a multi- dimensional space, we want to calculate the aggregate (e.g., count, average and sum) over the subset S_ of S such that for each p ∈ S_, Q has at least probability θ within the distance γ to p. We propose novel, efficient techniques to solve the problem following the filtering-and-verification paradigm. In particular, two novel filtering techniques are proposed to…
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Investigation and Analysis of New Approach of Intelligent Semantic Web Search Engines

Data mining
Name Investigation and Analysis of New Approach of Intelligent Semantic Web Search Engines Technology .net Category Data Mining Description As we know that www is allowing peoples to share the huge information from big database repositories. The amount of information grows billions of databases. Hence to search particular information from these huge databases we need specialized mechanism which helps to retrive that information efficiently. now days various types of search engines are available which makes information retrieving is difficult. but to provide the better solution to this proplem ,semantic web search engines are playing vital role.basically main aim of this kind of search engines is providing the required information is small time with maximum accuracy. IEEE Paper Yes IEEE Paper Year 2012 Contact Form [contact-form-7 id="71" title="Contact form 1"]
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Sequential Anomaly Detection in the Presence of Noise and Limited Feedback

Data mining
Name Sequential Anomaly Detection in the Presence of Noise and Limited Feedback Technology .net Category Data Mininig Description This paper describes a methodology for detecting anomalies from sequentially observed and potentially noisy data. The proposed approach consists of two main elements: (1) filtering, or assigning a belief or likelihood to each successive measurement based upon our ability to predict it from previous noisy observations, and (2) hedging, or flagging potential anomalies by comparing the current belief against a time-varying and data-adaptive threshold. The threshold is adjusted based on the available feedback from an end user. Our algorithms, which combine universal prediction with recent work on online convex programming, do not require computing posterior distributions given all current observations and involve simple primal-dual parameter updates. At the heart of the proposed…
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Clustering Methods in Data Mining with its Applications in High Education

Data mining
Name Clustering Methods in Data Mining with its Applications in High Education Technology .net Category Data Mining Description Data mining is a new technology, developing with database and artificial intelligence. It is a processing procedure of extracting credible, novel, effective and understandable patterns from database. Cluster analysis is an important data mining technique used to find data segmentation and pattern information. By clustering the data, people can obtain the data distribution, observe the character of each cluster, and make further study on particular clusters. In addition, cluster analysis usually acts as the preprocessing of other data mining operations. Therefore, cluster analysis has become a very active research topic in data mining. As the development of data mining, a number of clustering methods have been founded, The study of clustering technique…
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A Novel Algorithm for Automatic Document Clustering

Data mining
Name A Novel Algorithm for Automatic Document Clustering Technology .net Category Data Mining Description Internet has become an indispensible part of today’s life. World Wide Web (WWW) is the largest shared information source. Finding relevant information on the WWW is challenging. To respond to a user query, it is difficult to search through the large number of returned documents with the presence of today’s search engines. There is a need to organize a large set of documents into categories through clustering. The documents can be a user query or simply a collection of documents. Document clustering is the task of combining a set of documents into clusters so that intra cluster documents are similar to each other than inter cluster documents. Partitioning and Hierarchical algorithms are commonly used for document…
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Dynamic Personalized Recommendation on Sparse Data

Data mining
Name Dynamic Personalized Recommendation on Sparse Data Technology .net Category Data Mining Description Recommendation techniques are very important in the fields of E-commerce and other Web-based services. One of the main difficulties is dynamically providing high-quality recommendation on sparse data. In this paper, a novel dynamic personalized recommendation algorithm is proposed, in which information contained in both ratings and profile contents are utilized by exploring latent relations between ratings, a set of dynamic features are designed to describe user preferences in multiple phases, and finally a recommendation is made by adaptively weighting the features. Experimental results on public datasets show that the proposed algorithm has satisfying performance. IEEE Paper Yes IEEE Paper Year 2013 Contact Form [contact-form-7 id="71" title="Contact form 1"]
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Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases

Data mining
Name Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases Technology .net Category Data Mining Description Mining high utility itemsets from a transactional database refers to the discovery of itemsets with high utility like profits. Although a number of relevant algorithms have been proposed in recent years, they incur the problem of producing a large number of candidate itemsets for high utility itemsets. Such a large number of candidate itemsets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility itemsets. In this paper, we propose two algorithms, namely utility pattern growth (UP-Growth) and UP-Growth+, for mining high utility itemsets with a set of effective strategies for pruning candidate itemsets.…
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Sensitive Label Privacy Protection on Social Network Data

Data mining
Name Sensitive Label Privacy Protection on Social Network Data Technology .net Category Data Mining Description This paper is motivated by the recognition of the need for a ner grain and more personalized privacy in data publication of social networks. We propose a privacy protection scheme that not only prevents the disclosure of identity of users but also the disclosure of selected features in users' pro les. An individual user can select which features of her pro le she wishes to conceal. The social networks are modeled as graphs in which users are nodes and features are labels. Labels are denoted either as sensitive or as non-sensitive. We treat node labels both as background knowledge an adversary may possess, and as sensitive information that has to be protected. We present privacy protection algorithms…
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Privacy against Aggregate Knowledge Attacks

Data mining
Name Privacy against Aggregate Knowledge Attacks Technology .net Category Data Mining Description This paper focuses on protecting the privacy of individuals in publication scenarios where the attacker is ex- pected to have only abstract or aggregate knowledge about each record. Whereas, data privacy research usually focuses on defining stricter privacy guarantees that assume increasingly more sophisticated attack scenarios, it is also important to have anonymization methods and guarantees that will address any attack scenario. Enforcing a stricter guarantee than required increases unnecessarily the information loss. Consider for example the publication of tax records, where attackers might only know the total income, and not its con- stituent parts. Traditional anonymization methods would pro- tect user privacy by creating equivalence classes of identical records. Alternatively, in this work we propose an anonymization…
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Adapting a Ranking Model for Domain-Specific Search

Data mining
Name Adapting a Ranking Model for Domain-Specific Search Technology .net Category Data Mining Description An adaptation process is described to adapt a ranking model constructed for a broad-based search engine for use with a domain-specific ranking model. It’s difficult to applying the broad-based ranking model directly to different domains due to domain differences, to build a unique ranking model for each domain it time-consuming for training models. In this paper,we address these difficulties by proposing algorithm called ranking adaptation SVM (RA-SVM), Our algorithm only requires the prediction from the existing ranking models, rather than their internal representations or the data from auxiliary domains The ranking model is adapted for use in a search environment focusing on a specific segment of online content, for example, a specific topic, media type, or…
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Efficient Similarity Search over Encrypted Data

Data mining
Name Efficient Similarity Search over Encrypted Data Technology .net Category Data Mining Description amount of data have been stored in the cloud. Although cloud based services offer many advantages, privacy and security of the sensitive data is a big concern. To mitigate the concerns, it is desirable to outsource sensitive data in encrypted form. Encrypted storage protects the data against illegal access, but it complicates some basic, yet important functionality such as the search on the data. To achieve search over encrypted data without compromising the privacy, considerable amount of searchable encryption schemes have been proposed in the literature. However, almost all of them handle exact query matching but not similarity matching; a crucial requirement for real world applications. Although some sophisticated secure multi-party computation based cryptographic techniques are available…
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A Bayesian Approach to Filtering Junk E-Mail

Data mining
Name A Bayesian Approach to Filtering Junk E-Mail Technology Java Category Data Mining Description Abstract In addressing the growing problem of junk E-mail on the Internet, we examine methods for the automated construction of lters to eliminate such unwanted mes- sages from a user's mail stream. By casting this prob- lem in a decision theoretic framework, we are able to make use of probabilistic learning methods in conjunc- tion with a notion of di erential misclassi cation cost to produce lters which are especially appropriate for the nuances of this task. While this may appear, at rst, to be a straight-forward text classi cation prob- lem, we show that by considering domain-speci c fea- tures of this problem in addition to the raw text of E-mail messages, we can produce much more accurate lters.…
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Opinion Mining for web search

Data mining
Name Opinion Mining for web search Technology .net Category Data Mining Description Generally, search engine retrieves the information using Page Rank, Distance vector algorithm, crawling, etc. on the basis of the user’s query. But it may happen that the links retrieved by search engine are may or may not be exactly related to the user’s query and user has to check all the links to know whether the needed information is present in the document or not, it becomes a tedious and time consuming job for the user. Our focus is to cluster different documents based on subjective similarities and dissimilarities. Our proposed tool ‘Web Search Miner’  which is based on the concept of  user opinions mining, which uses k-means search algorithm and distance measure based on Term frequency &…
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Distributed Association rule mining : Market basket Analysis

Data mining
Name Distributed Association rule mining : Market basket Analysis Technology .net Category Data Mining Description Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. The automated, prospective analyses offered by data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems. Data mining tools can answer business questions that traditionally were too time consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations. IEEE Paper Yes IEEE Paper Year 2012 Contact Form [contact-form-7…
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web usage mining using apriori

Data mining
Name web usage mining using apriori Technology .net Category .net Description The enormous content of information on the World Wide Web makes it obvious candidate for data mining research. Application of data mining techniques to the World Wide Web referred as Web mining where this term has been used in three distinct ways; Web Content Mining, Web Structure Mining and Web Usage Mining. E Learning is one of the Web based application where it will facing with large amount of data. In order to produce the E-Learning  portal usage patterns and user behaviors, this paper implements the high level process of Web Usage Mining using advance Association Rules algorithm  call D-Apriori Algorithm. Web Usage Mining consists of three main phases, namely Data Preprocessing, Pattern Discovering and Pattern Analysis. Server log…
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Sales & Inventory Prediction using Data Mining

Data mining
Name  Sales & Inventory Prediction using Data Mining Technology .net Category Data Mining Description Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. The automated, prospective analyses offered by data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems. Data mining tools can answer business questions that traditionally were too time consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations. IEEE Paper Yes IEEE Paper Year 2012 Contact Form [contact-form-7 id="71"…
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