Tag: Dot NET

Dot NET

10Jul 2015 by chintan No Comments

Facilitating Document Annotation Using Content and Querying Value

Data mining, Web | Desktop Application

Facilitating Document Annotation Using Content and Querying Value 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, if prompted by the interface; or that it is much easier…

10Jul 2015 by chintan No Comments

Context-Based Diversification for Keyword Queries Over XML Data

Data mining, Web | Desktop Application

Context-Based Diversification for Keyword Queries Over XML Data 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 targeted: the k selected query candidates are most relevant to…

10Jul 2015 by chintan No Comments

Customizable Pointof- Interest Queries in Road Networks

Data mining, Web | Desktop Application

Customizable Pointof- Interest Queries in Road Networks 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.

10Jul 2015 by chintan No Comments

Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions

Data mining, Web | Desktop Application

Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions 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.

10Jul 2015 by chintan No Comments

Tweet Segmentation and Its Application to Named Entity Recognition

Data mining, Web | Desktop Application

Tweet Segmentation and Its Application to Named Entity Recognition 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 being a phrase within the batch of tweets (i.e., local…

10Jul 2015 by chintan No Comments

Co-Extracting Opinion Targets and Opinion Words from Online Reviews Based on the Word Alignment Model

Data mining, Web | Desktop Application

Co-Extracting Opinion Targets and Opinion Words from Online Reviews Based on the Word Alignment Model 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 alignment model effectively alleviates the negative effects of parsing errors…

10Jul 2015 by chintan No Comments

Polarity Consistency Checking for Domain Independent Sentiment Dictionaries

Data mining, Web | Desktop Application

Polarity Consistency Checking for Domain Independent Sentiment Dictionaries 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.

10Jul 2015 by chintan No Comments

RRW—A Robust and Reversible Watermarking Technique for Relational Data

Data mining, Web | Desktop Application

RRW—A Robust and Reversible Watermarking Technique for Relational Data 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, reversible watermarking is required that ensures; (i) watermark encoding and decoding by…

09Jul 2015 by chintan No Comments

A Location- and Diversity-aware News Feed System for Mobile Users

Android Mobile development, Security and Encryption

A Location- and Diversity-aware News Feed System for Mobile Users A location-aware news feed system enables mobile users to share geo-tagged user-generated messages, e.g., a user can receive nearby messages that are the most relevant to her. In this paper, we present MobiFeed that is a framework designed for scheduling news feeds for mobile users. MobiFeed consists of three key functions, location prediction, relevance measure, and news feed scheduler. The location prediction function is designed to predict a mobile user’s locations based on an existing path prediction algorithm. The relevance measure function is implemented by combining the vector space model with non-spatial and spatial factors to determine the relevance of a message to a user. The news feed scheduler works with the other two functions to generate news feeds for…

21Jul 2014 by chintan

Design of a Secured E-voting System

Android Mobile development

Design of a Secured E-voting System E-voting systems are becoming popular with the widespread use of computers and embedded systems. Security is the vital issue should be considered in such systems. This paper proposes a new e-voting system that fulfills the security requirements of e-voting. It is based on homomorphic property and blind signature scheme. The proposed system is implemented on an embedded system which serves as a voting machine. The system employes RFID to store all conditions that comply with the rule of the government to check voter eligibility.

21Jul 2014 by chintan

Shopping Application System With Near Field Communication (NFC) Based on Android

Android Mobile development, Web | Desktop Application

Shopping Application System With Near Field Communication (NFC) Based on Android The rapid development of mobile communications systems today, along with the changing times and technology, both in terms of hardware, operating system used and the use of Internet bandwidth, making some mobile applications also contribute to exploit these developments. Mobile Commerce Applications for an example, became the most popular applications for mobile users who do not want to trouble yourself with having to carry cash everywhere. An important technology behind mobile payments is called Near Field Communication (NFC). As an indication that NFC represents the potential and tremendous business, leading companies such as Nokia, Microsoft and NXP Semiconductors, actively engaged in the NFC Forum. Shopping application process integrated with NFC technologybased on Android. Shopping application system designed, for the…

21Jul 2014 by chintan

Developing an Android based Learning Application for Mobile Devices

Android Mobile development

Developing an Android based Learning Application for Mobile Devices his paper is about the development of MLEA, a platform that assists, through Android cellphones and tablets, the mobility of users of learning virtual environments. MLEA is an application that implements computational techniques such as web services, design patterns, ontologies, and mobile computational techniques in order to allow the communication between mobile devices and the content management system – Moodle. It´s based on a service oriented, client server architecture that combines the REST protocol and JSON format for data interchange. The client will be provided with features for alerts, file downloads, chats and forums, grade books, quizzes, and calendar, among others.

21Jul 2014 by chintan

Location Based Reminder Using GPS For Mobile

Android Mobile development

Location Based Reminder Using GPS For Mobile Although location-based reminder applications have been widely prototyped, there are few results regarding their impact on people: how are they used, do they change people’s behavior and what features influence usefulness the most. Cell phones provide a compelling platform for the delivery of location-based reminders within a user's everyday natural context. We present requirements for location-based reminders resulting from a qualitative study performed at small area in the city, and elaborate how these results are influencing ongoing design of a more comprehensive location-based reminder system. In this paper we propose an architecture of location based services which uses GPS. Within the architecture, we discuss the challenges for context management, service trigger mechanism and preference-based services.

19Jul 2014 by chintan No Comments

Learn to Personalized Image Search from the Photo Sharing Websites

Multimedia, Web | Desktop Application

Learn to Personalized Image Search from the Photo Sharing Websites Increasingly developed social sharing websites, like Flickr and Youtube, allow users to create, share, annotate and comment Medias. The large-scale usergenerated meta-data not only facilitate users in sharing and organizing multimedia content, but provide useful information to improve media retrieval and management. Personalized search serves as one of such examples where the web search experience is improved by generating the returned list according to the modified user search intents. In this paper, we exploit the social annotations and propose a novel framework simultaneously considering the user and query relevance to learn to personalized image search. The basic premise is to embed the user preference and query-related search intent into user-specific topic spaces. Since the users’ original annotation is too sparse…

19Jul 2014 by chintan No Comments

Trust modeling in social tagging of multimedia content.

Trust modeling in social tagging of multimedia content. Tagging in online social networks is very popular these days, as it facilitates search and retrieval of multimedia content. However, noisy and spam annotations often make it difficult to perform an efficient search. Users may make mistakes in tagging and irrelevant tags and content may be maliciously added for advertisement or self-promotion. This article surveys recent advances in techniques for combatting such noise and spam in social tagging. We classify the state-of-the-art approaches into a few categories and study representative examples in each. We also qualitatively compare and contrast them and outline open issues for future research.

19Jul 2014 by chintan No Comments

Persuasive Cued Click-Points: Design, implementation, and evaluation of a knowledge-based authentica

Multimedia, Security and Encryption

Persuasive Cued Click-Points: Design, implementation, and evaluation of a knowledge-based authentication Increasingly developed social sharing websites, like Flickr and Youtube, allow users to create, share, annotate and comment Medias. The large-scale usergenerated meta-data not only facilitate users in sharing and organizing multimedia content, but provide useful information to improve media retrieval and management. Personalized search serves as one of such examples where the web search experience is improved by generating the returned list according to the modified user search intents. In this paper, we exploit the social annotations and propose a novel framework simultaneously considering the user and query relevance to learn to personalized image search. The basic premise is to embed the user preference and query-related search intent into user-specific topic spaces. Since the users’ original annotation is too…

19Jul 2014 by chintan No Comments

BECAN: A Bandwidth-Efficient Cooperative Authentication Scheme for Filtering Injected False Data in

Parallel And Distributed System

BECAN: A Bandwidth-Efficient Cooperative Authentication Scheme for Filtering Injected False Data in Injecting false data attack is a well known serious threat to wireless sensor network, for which an adversary reports bogus information to sink causing error decision at upper level and energy waste in en-route nodes. In this paper, we propose a novel bandwidth-efficient cooperative authentication (BECAN) scheme for filtering injected false data. Based on the random graph characteristics of sensor node deployment and the cooperative bit-compressed authentication technique, the proposed BECAN scheme can save energy by early detecting and filtering the majority of injected false data with minor extra overheads at the en-route nodes. In addition, only a very small fraction of injected false data needs to be checked by the sink, which thus largely reduces the burden…

19Jul 2014 by chintan No Comments

Privacy-Preserving Updates to Anonymous and Confidential Databases

Parallel And Distributed System, Web | Desktop Application

Privacy-Preserving Updates to Anonymous and Confidential Databases Suppose Alice owns a k-anonymous database and needs to determine whether her database, when inserted with a tuple owned by Bob, is still k-anonymous. Also, suppose that access to the database is strictly controlled, because for example data are used for certain experiments that need to be maintained conﬁdential. Clearly, allowing Alice to directly read the contents of the tuple breaks the privacy of Bob (e.g., a patient’s medical record); on the other hand, the conﬁdentiality of the database managed by Alice is violated once Bob has access to the contents of the database. Thus, the problem is to check whether the database inserted with the tuple is still k-anonymous, without letting Alice and Bob know the contents of the tuple and the…

19Jul 2014 by chintan No Comments

The Geometric Efficient Matching Algorithm for Firewalls

Parallel And Distributed System, Web | Desktop Application

The Geometric Efficient Matching Algorithm for Firewalls The firewall is one of the central technologies allowing high-level access control to organization networks. Packet matching in firewalls involves matching on many fields from the TCP and IP packet header. At least five fields (protocol number, source and destination IP addresses, and ports) are involved in the decision which rule applies to a given packet. With available bandwidth increasing rapidly, very efficient matching algorithms need to be deployed in modern firewalls to ensure that the firewall does not become a bottleneck Since firewalls need to filter all the traffic crossing the network perimeter, they should be able to sustain a very high throughput, or risk becoming a bottleneck. Thus, algorithms from computational geometry can be applied. In this paper we consider a…

19Jul 2014 by chintan No Comments

In Cloud, Can Scientific Communities Benefit from the Economies of Scale?

Parallel And Distributed System, Web | Desktop Application

In Cloud, Can Scientific Communities Benefit from the Economies of Scale? The basic idea behind Cloud computing is that resource providers offer elastic resources to end users. In this paper, we intend to answer one key question to the success of Cloud computing: in Cloud, can small or medium-scale scientific computing communities benefit from the economies of scale? Our research contributions are three fold: first, we propose an enhanced scientific public cloud model (ESP) that encourages small or medium scale research organizations rent elastic resources from a public cloud provider; second, on a basis of the ESP model, we design and implement the Dawning Cloud system that can consolidate heterogeneous scientific workloads on a Cloud site; third, we propose an innovative emulation methodology and perform a comprehensive evaluation. We found…

19Jul 2014 by chintan No Comments

A NOVEL ANTI PHISHING FRAMEWORK BASED ON VISUAL CRYPTOGRAPHY

Parallel And Distributed System, Security and Encryption, Web | Desktop Application

A NOVEL ANTI PHISHING FRAMEWORK BASED ON VISUAL CRYPTOGRAPHY Phishing is an attempt by an individual or a group to thieve personal confidential information such as passwords, credit card information etc from unsuspecting victims for identity theft, financial gain and other fraudulent activities. In this paper we have proposed a new approach named as "A Novel Anti phishing framework based on visual cryptography" to solve the problem of phishing. Here an image based authentication using Visual Cryptography (vc) is used. The use of visual cryptography is explored to preserve the privacy of image captcha by decomposing the original image captcha into two shares that are stored in separate database servers such that the original image captcha can be revealed only when both are simultaneously available; the individual sheet images do…

19Jul 2014 by chintan No Comments

Balancing the Tradeoffs between Query Delay and Data Availability in MANETs.

Parallel And Distributed System, Web | Desktop Application

Balancing the Tradeoffs between Query Delay and Data Availability in MANETs. In mobile ad hoc networks (MANETs), nodes move freely and link/node failures are common, which leads to frequent network partitions. When a network partition occurs, mobile nodes in one partition are not able to access data hosted by nodes in other partitions, and hence significantly degrade the performance of data access. To deal with this problem, we apply data replication techniques. Existing data replication solutions in either wired or wireless networks aim at either reducing the query delay or improving the data availability, but not both. As both metrics are important for mobile nodes, we propose schemes to balance the tradeoffs between data availability and query delay under different system settings and requirements. Extensive simulation results show that the…

19Jul 2014 by chintan No Comments

Resource-Aware Application State Monitoring.

Parallel And Distributed System

Resource-Aware Application State Monitoring. The increasing popularity of large-scale distributed applications in datacenters has led to the growing demand of distributed application state monitoring. These application state monitoring tasks often involve collecting values of various status attributes from a large number of nodes. One challenge in such large-scale application state monitoring is to organize nodes into a monitoring overlay that achieves monitoring scalability and cost-effectiveness at the same time. In this paper, we present REMO, a REsource-aware application state MOnitoring system, to address the challenge of monitoring overlay construction. REMO distinguishes itself from existing works in several key aspects. First, it jointly considers inter-task costsharing opportunities and node-level resource constraints. Furthermore, it explicitly models the per-message processing overhead which can be substantial but is often ignored by previous works. Second,…

19Jul 2014 by chintan No Comments

SPOC: A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emerge

Parallel And Distributed System, Web | Desktop Application

SPOC: A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emerge With the pervasiveness of smart phones and the advance of wireless body sensor networks (BSNs), mobile Healthcare (m-Healthcare), which extends the operation of Healthcare provider into a pervasive environment for better health monitoring, has attracted considerable interest recently. However, the flourish of m-Healthcare still faces many challenges including information security and privacy preservation. In this paper, we propose a secure and privacy-preserving opportunistic computing framework, called SPOC, for m-Healthcare emergency. With SPOC, smart phone resources including computing power and energy can be opportunistically gathered to process the computing intensive personal health information (PHI) during m-Healthcare emergency with minimal privacy disclosure. In specific, to leverage the PHI privacy disclosure and the high reliability of PHI process and transmission in m-Healthcare…

19Jul 2014 by chintan No Comments

Cooperative Provable Data Possession for Integrity Verification in Multi-Cloud Storage.

Parallel And Distributed System, Web | Desktop Application

Cooperative Provable Data Possession for Integrity Verification in Multi-Cloud Storage. Provable data possession (PDP) is a technique for ensuring the integrity of data in storage outsourcing. In this paper, we address the construction of an efficient PDP scheme for distributed cloud storage to support the scalability of service and data migration, in which we consider the existence of multiple cloud service providers to cooperatively store and maintain the clients’ data. We present a cooperative PDP (CPDP) scheme based on homomorphic verifiable response and hash index hierarchy. We prove the security of our scheme based on multi-prover zero-knowledge proof system, which can satisfy completeness, knowledge soundness, and zero-knowledge properties. In addition, we articulate performance optimization mechanisms for our scheme, and in particular present an efficient method for selecting optimal parameter values…

19Jul 2014 by chintan

OCRAndroid: A Framework to Digitize Text Using Mobile Phones

Android Mobile development

OCRAndroid: A Framework to Digitize Text Using Mobile Phones As demand grows for mobile phone applications, research in optical character recognition, a technology well developed for scanned documents, is shifting focus to the recognition of text embedded in digital photographs. In this paper, we present OCRdroid, a generic framework for developing OCR-based applications on mobile phones. OCRdroid combines a light-weight image preprocessing suite installed inside the mobile phone and an OCR engine connected to a backend server. We demonstrate the power and functionality of this framework by implementing two applications called PocketPal and PocketReader based on OCRdroid on HTC Android G1 mobile phone. Initial evaluations of these pilot experiments demonstrate the potential of using OCRdroid framework for realworld OCR-based mobile applications.

19Jul 2014 by chintan

Mobile Phone Based Drunk Driving Detection

Android Mobile development

Mobile Phone Based Drunk Driving Detection Drunk driving, or officially Driving Under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world. In this paper, we propose a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution requires only a mobile phone placed in vehicle and with accelerometer and orientation sensor. A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with typical drunk driving patterns extracted from real driving tests. Once any evidence of drunk driving is present, the mobile phone will automatically alert the driver or call the police for help well before accident actually happens. We implement the detection system on Android G1 phone…

19Jul 2014 by chintan

Android based elimination of potholes

Android Mobile development, Web | Desktop Application

Android based elimination of potholes Its a web based project where user or normal residential people can complain about their nearby potholes. They can take an image of it and upload it to submit to BMC department. Every user will have their own credentials to login and to view the potholes. BMC will have their own admin login details to look after the posting and tackle or reply to each complaints so that they can sort those problem as soon as possible.

19Jul 2014 by chintan

A Personalized Mobile Search Engine

Android Mobile development

A Personalized Mobile Search Engine We propose a personalized mobile search engine, PMSE, that captures the users’ preferences in the form of concepts by mining their clickthrough data. Due to the importance of location information in mobile search, PMSE classifies these concepts into content concepts and location concepts. In addition, users’ locations (positioned by GPS) are used to supplement the location concepts in PMSE. The user preferences are organized in an ontology-based, multi-facet user profile, which are used to adapt a personalized ranking function for rank adaptation of future search results. To characterize the diversity of the concepts associated with a query and their relevances to the users need, four entropies are introduced to balance the weights between the content and location facets. Based on the client-server model, we also…

19Jul 2014 by chintan

Designing the Next Generation of Mobile Tourism Application based on Situation Awareness

Android Mobile development

Designing the Next Generation of Mobile Tourism Application based on Situation Awareness Mobile tourism applications are changing the way travelers plan and experience tourism in the years to come. A large and growing body of literature has investigated the development of context awareness mobile applications for tourism industry. Various aspects of context awareness are studied and applied in tour guide companions and recommendation systems. However, these context awareness mobile applications do not improve traveler’s situation awareness especially in pre-visiting and during visiting phases. In other words, when using mobile applications, travelers may not perceive the situation correctly, fail to comprehend the situation or they are unable to anticipate the future development. This paper proposes a theoretical approach for designing mobile tourism applications using situation awareness. Three scenarios of traveler visiting…

19Jul 2014 by chintan

Semisupervised Biased Maximum Margin Analysis for Interactive Image Retrieval.

Image Processing

Semisupervised Biased Maximum Margin Analysis for Interactive Image Retrieval. With many potential practical applications, content- based image retrieval (CBIR) has attracted substantial attention during the past few years. A variety of relevance feedback (RF) schemes have been developed as a powerful tool to bridge the semantic gap between low-level visual features and high-level semantic concepts, and thus to improve the performance of CBIR systems. Among various RF approaches, support-vector-machine (SVM)-based RF is one of the most popular techniques in CBIR. Despite the success, directly using SVM as an RF scheme has two main drawbacks. First, it treats the positive and negative feedbacks equally, which is not appropriate since the two groups of training feedbacks have distinct properties. Second, most of the SVM-based RF techniques do not take into account the…

19Jul 2014 by chintan

Scalable Face Image Retrieval using Attribute-Enhanced Sparse Codewords

Image Processing, Web | Desktop Application

Scalable Face Image Retrieval using Attribute-Enhanced Sparse Codewords Photos with people (e.g., family, friends, celebrities, etc.) are the major interest of users. Thus, with the exponentially growing photos, large-scale content-based face image retrieval is an enabling technology for many emerging applications. In this work, we aim to utilize automatically detected human attributes that contain semantic cues of the face photos to improve content- based face retrieval by constructing semantic codewords for effi-cient large-scale face retrieval. By leveraging human attributes in a scalable and systematic framework, we propose two orthogonal methods named attribute-enhanced sparse coding and attribute- embedded inverted indexing to improve the face retrieval in the offline and online stages. We investigate the effectiveness of different attributes and vital factors essential for face retrieval. Experimenting on two public datasets, the…

19Jul 2014 by chintan

An effective image steganalysis method based on neighborhood information of pixels

Image Processing, Web | Desktop Application

An effective image steganalysis method based on neighborhood information of pixels This project focuses on image steganalysis. We use higher order image statistics based on neighborhood information of pixels (NIP) to detect the stego images from original ones. We use subtracting gray values of adjacent pixels to capture neighborhood information, and also make use of ―rotation invariant‖ property to reduce the dimensionality for the whole feature sets. We tested two kinds of NIP feature, the experimental results illustrates that our proposed feature sets are with good performance and even outperform the state-of-art in certain aspect.

19Jul 2014 by chintan

Automatic Plant Leaf Classification for a Mobile Field Guide

Image Processing

Automatic Plant Leaf Classification for a Mobile Field Guide In this paper we describe the development of an Android application that gives users the ability to identify plant species based on photographs of the plant’s leaves taken with a mobile phone. At the heart of this application is an algorithm that acquires morphological features of the leaves, computes welldocumented metrics such as the angle code histogram (ACH), then classifies the species based on a novel combination of the computed metrics. The algorithm is first trained against several samples of known plant species and then used to classify unknown query species. Aided by features designed into the application such as touchscreen image rotation and contour preview, the algorithm is very successful in properly classifying species contained in the training library.

19Jul 2014 by chintan No Comments

Fuzzy Keyword Search over Encrypted Data in Cloud Computing

Cloud Computing

Fuzzy Keyword Search over Encrypted Data in Cloud Computing As Cloud Computing becomes prevalent, more and more sensitive information are being centralized into the cloud. Although traditional searchable encryption schemes allow a user to securely search over encrypted data through keywords and selectively retrieve files of interest, these techniques support only exact keyword search. In this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy. Fuzzy keyword search greatly enhances system usability by returning the matching files when users’ searching inputs exactly match the predefined keywords or the closest possible matching files based on keyword similarity semantics, when exact match fails. In our solution, we exploit edit distance to quantify keywords similarity and develop two…

19Jul 2014 by chintan

Secure And Authenticated Reversible Data Hiding In Encrypted Images

Image Processing, Web | Desktop Application

Secure And Authenticated Reversible Data Hiding In Encrypted Images Reversible data hiding a novel technique which is used to embed additional information in the encrypted images, applies in military and medical images, which can be recoverable with original media and the hided data without loss. A number of reversible data hiding techniques were proposed in the recent years, but on analysis, all lacks in providing the security and authentication. This project proposes a novel reversible data hiding technique which work is separable, the receiver can extract the original image or extra embedded data or both according to the keys hold by the receiver. On the other hand the receiver can verify the data hided by the data hider, such that the work proposes both security and authentication. This project proposes…

19Jul 2014 by chintan No Comments

Developing Secure Social Healthcare System over the Cloud

Cloud Computing, Web | Desktop Application

Developing Secure Social Healthcare System over the Cloud Healthcare application is a social media application which is developed over the cloud. Now a day we hear two cutting edge technologies most social media and cloud computing. Developing and maintaining a healthcare system with self infrastructure well cost more. Many small hospitals save hard copies of patient’s records. This healthcare application will provide web service which is developed over the cloud so it well reduces the cost and they need not be worried about infrastructure. Cloud providers well provide up to date software so, software well be up to date. Since data is present in the cloud most of them worry about security. By using role based access control healthcare system is secured.

19Jul 2014 by chintan

An extended visual cryptography scheme without pixel expansion for halftone images

Image Processing, Web | Desktop Application

An extended visual cryptography scheme without pixel expansion for halftone images Visual cryptography is a secret sharing scheme which use images distributed as shares such that, when the shares are superimposed, a hidden secret image is revealed. In extended visual cryptography, the share images are constructed to contain meaningful cover images, thereby providing opportunities for integrating visual cryptography and biometric security techniques. In this paper, we propose a method for processing halftone images that improves the quality of the share images and the recovered secret image in an extended visual cryptography scheme for which the size of the share images and the recovered image is the same as for the original halftone secret image. The resulting scheme maintains the perfect security of the original extended visual cryptography approach.

19Jul 2014 by chintan

A Secret-Sharing-Based Method for Authentication of Grayscale Document Images via the Use of the PNG

Image Processing, Web | Desktop Application

A Secret-Sharing-Based Method for Authentication of Grayscale Document Images via the Use of the PNG Abstract—A new blind authentication method based on the secret sharing technique with a data repair capability for grayscale document images via the use of the PNG image is proposed. An authentication signal is generated for each block of a grayscale document image, which, together with the binarized block content, is transformed into several shares using the Shamir secret sharing scheme. The involved parameters are carefully chosen so that as many shares as possible are generated and embedded into an alpha channel plane. The alpha channel plane is then combined with the original grayscale image to form a PNG image. During the embedding process, the computed share values are mapped into a range of alpha channel…

19Jul 2014 by chintan

Robust Face-Name Graph Matching for Movie Character Identification

Image Processing, Web | Desktop Application

Robust Face-Name Graph Matching for Movie Character Identification Automatic face identification of characters in movies has drawn significant research interests and led to many interesting applications. It is a challenging problem due to the huge variation in the appearance of each character. Although existing methods demonstrate promising results in clean environment, the performances are limited in complex movie scenes due to the noises generated during the face tracking and face clustering process. In this paper we present two schemes of global face-name matching based framework for robust character identification. The contributions of this work include: 1) A noise insensitive character relationship representation is incorporated. 2) We introduce an edit operation based graph matching algorithm. 3) Complex character changes are handled by simultaneously graph partition and graph matching. 4) Beyond existing…

19Jul 2014 by chintan

A DYMANIC METHOD TO SECURE CONFIDENTIAL DATA USING SIGNCRYPTION WITH STEGANOGRAPHY

Image Processing, Web | Desktop Application

A DYMANIC METHOD TO SECURE CONFIDENTIAL DATA USING SIGNCRYPTION WITH STEGANOGRAPHY Since years due to the increase of technology, the means of communication and transferring information from one point to the other has been drastically changed. Because of this rapid development of technology, few people misusing the technology to unveil the confidential data. To provide high end security to the data to prevent form the attackers we are proposing a dynamic method in this paper. Two things are important to provide security to the data confidentiality and encryption. In this paper we are using signcryption technique to provide high security to the data, by encrypting the data with digital signature, because of this the attacker cannot do any kind of modification to the data in case the data is decrypted…

19Jul 2014 by chintan

Mitigating of fire based disaster using IP

Image Processing, Web | Desktop Application

Mitigating of fire based disaster using IP Present work is an in depth study to detect flames in video by processing the data captured by an ordinary camera. Previous vision based methods were based on color difference, motion detection of flame pixel and flame edge detection. This paper focuses on optimizing the flame detection by identifying gray cycle pixels nearby the flame, which is generated because of smoke and of spreading of fire pixel and the area spread of flame. These techniques can be used to reduce false alarms along with fire detection methods . The novel system simulate the existing fire detection techniques with above given new techniques of fire detection and give optimized way to detect the fire in terms of less false alarms by giving the accurate…

19Jul 2014 by chintan

A Novel Data Embedding Method Using Adaptive Pixel Pair Matching

Image Processing, Web | Desktop Application

A Novel Data Embedding Method Using Adaptive Pixel Pair Matching This paper proposes a new data-hiding method based on pixel pair matching (PPM). The basic idea of PPM is to use the values of pixel pair as a reference coordinate, and search a coordinate in the neighborhood set of this pixel pair according to a given message digit. The pixel pair is then replaced by the searched coordinate to conceal the digit. Exploiting modiﬁcation direction (EMD) and diamond encoding (DE) are two data-hiding methods proposed recently based on PPM. The maximum capacity of EMD is 1.161 bpp and DE extends the payload of EMD by embedding digits in a larger notational system. The proposed method offers lower distortion than DE by providing more compact neighborhood sets and allowing embedded digits…

19Jul 2014 by chintan

A Keyless Approach to Image Encryption

Image Processing, Security and Encryption, Web | Desktop Application

A Keyless Approach to Image Encryption Maintaining the secrecy and confidentiality of images is a vibrant area of research, with two different approaches being followed, the first being encrypting the images through encryption algorithms using keys, the other approach involves dividing the image into random shares to maintain the images secrecy. Unfortunately heavy computation cost and key management limit the employment of the first approach and the poor quality of the recovered image from the random shares limit the applications of the second approach. In this paper we propose a novel approach without the use of encryption keys. The approach employs Sieving, Division and Shuffling to generate random shares such that with minimal computation, the original secret image can be recovered from the random shares without any loss of image…

19Jul 2014 by chintan

N-Square Approach For Lossless Image Compression And Decompression

Image Processing, Web | Desktop Application

N-Square Approach For Lossless Image Compression And Decompression There are several lossy and lossless coding techniques developed all through the last two decades. Although very high compression can be achieved with lossy compression techniques, they are deficient in obtaining the original image. While lossless compression technique recovers the image exactly. In applications related to medical imaging lossless techniques are required, as the loss of information is deplorable. The objective of image compression is to symbolize an image with a handful number of bits as possible while preserving the quality required for the given application. In this paper we are introducing a new lossless encoding and decoding technique which even better reduces the entropy there by reducing the average number of bits with the utility of Non Binary Huffman coding through…

19Jul 2014 by chintan

An Efficient Real Time Moving Object Detection Method for Video Surveillance System

Image Processing, Web | Desktop Application

An Efficient Real Time Moving Object Detection Method for Video Surveillance System Moving object detection has been widely used in diverse discipline such as intelligent transportation systems, airport security systems, video monitoring systems, and so on. In this paper, we propose an efficient moving object detection method using enhanced edge localization mechanism and gradient directional masking for video surveillance system. In our proposed method, gradient map images are initially generated from the input and background images using a gradient operator. The gradient difference map is then calculated from gradient map images. The moving object is then detected by using appropriate directional masking and thresholding. Simulation results indicate that the proposed method consistently performs well under different illumination conditions including indoor, outdoor, sunny, and foggy cases. Moreover, it outperforms well known…

19Jul 2014 by chintan

Image Authentication and Restoration using BlockWise Fragile Watermarking based on k-Medoids Clustering Approach

Image Processing, Web | Desktop Application

Image Authentication and Restoration using BlockWise Fragile Watermarking based on k-Medoids Clustering Approach This paper proposes a block-wise fragile watermarking scheme based on k-medoids clustering approach. Proposed scheme is effective enough to reconstruct the tampered extensive content of an image. According to the suggested algorithm, first of all image is divided into the blocks and forty eight bits are calculated for each block, which consist of forty five Recovery bits and three Authentication bits namely Union bit, Affiliation bit and Spectrum bit. Authentication bits for a particular block are calculated by extracting five MSBs from each pixel of that block and apply them, on some predefined hash functions. Forty five Recovery bits are calculated using the means of derived clusters and its corresponding mapping bits. These Forty eight bits for…

19Jul 2014 by chintan

A robust skew detection method based on maximum gradient difference and R-signature

Image Processing, Web | Desktop Application

A robust skew detection method based on maximum gradient difference and R-signature In this paper we study the detection of skewed text lines in scanned document images. The aim of our work is to develop a new automatic approach able to estimate precisely the skew angle of text in document images. Our new method is based on Maximum Gradient Difference (MGD) and R-signature. It detects zones that have high variations of gray values in different directions using the MGD transform. We consider these zones as being text regions. R-signature which is a shape descriptor based on Radon transform is then applied in order to approximate the skew angle. The accuracy of the proposed algorithm is evaluated on an open dataset by comparing error rates.

19Jul 2014 by chintan

Image-based object detection under varying illumination in environments with specular surfaces

Image Processing, Web | Desktop Application

Image-based object detection under varying illumination in environments with specular surfaces Image-based environment representations capture the appearance of the surroundings of a mobile robot and are useful for the detection of novelty. However, image-based novelty detection can be impaired by illumination effects. In this paper we present an approach for the image-based detection of novel objects in a scene under varying lighting conditions and in the presence of objects with specular surfaces. The computation of an illumination-invariant image-based environment representation allows for the extraction of the shading of the environment from camera images. Using statistical models infered from the luminance and the saturation component of the shading images, secularities and shadows are detected and suppressed in the process of novelty detection. Experimental results show that the proposed method outperforms two…

19Jul 2014 by chintan

A New Block Compressive Sensing to Control the Number of Measurements

Image Processing, Web | Desktop Application

A New Block Compressive Sensing to Control the Number of Measurements Compressive Sensing (CS) aims to recover a sparse signal from a small number of projections onto random vectors. Be- cause of its great practical possibility, both academia and in- dustries have made efforts to develop the CS’s reconstruction performance, but most of existing works remain at the theo- retical study. In this paper, we propose a new Block Compres- sive Sensing (nBCS), which has several benefits compared to the general CS methods. In particular, the nBCS can be dynamically adaptive to varying channel capacity because it conveys the good inheritance of the wavelet transform.

19Jul 2014 by chintan No Comments

Secure Authentication using Image Processing and Visual Cryptography for Banking Applications

Image Processing, Web | Desktop Application

Secure Authentication using Image Processing and Visual Cryptography for Banking Applications Core banking is a set of services provided by a group of networked bank branches. Bank customers may access their funds and perform other simple transactions from any of the member branch ofces. The major issue in core banking is the authenticity of the customer. Due to unavoidable hacking of the databases on the internet, it is always quite difcult to trust the information on the internet. To solve this problem of authentication, we are proposing an algorithm based on image processing and visual cryptography. This paper proposes a technique of processing the signature of a customer and then dividing it into shares. Total number of shares to be created is depending on the scheme chosen by the bank.…

19Jul 2014 by chintan No Comments

An Algorithm to Automatically Generate Schedule for School Lectures Using a Heuristic Approach

Web | Desktop Application

An Algorithm to Automatically Generate Schedule for School Lectures Using a Heuristic Approach This paper proposes a general solution for the School timetabling problem. Most heuristic proposed earlier approaches the problem from the students’ point of view. This solution, however, works from the teachers’ point of view i.e. teacher availability for a given time slot. While all the hard constraints (e.g. the availability of teachers, etc.) are resolved rigorously, the scheduling solution presented in this paper is an adaptive one, with a primary aim to solve the issue of clashes of lectures and subjects, pertaining to teachers.

19Jul 2014 by chintan No Comments

A Mixed Reality Virtual Clothes Try-On System

Web | Desktop Application

A Mixed Reality Virtual Clothes Try-On System Virtual try-on of clothes has received much attention recently due to its commercial potential. It can be used for online shopping or intelligent recommendation to narrow down the selections to a few designs and sizes. In this paper, we present a mixed reality system for 3D virtual clothes try-on that enables a user to see herself wearing virtual clothes while looking at a mirror display, without taking off her actual clothes. The user can select various virtual clothes for trying-on. The system physically simulates the selected virtual clothes on the user's body in real-time and the user can see virtual clothes fitting on the her mirror image from various angles as she moves. The major contribution of this paper is that we automatically…

19Jul 2014 by chintan No Comments

Knowledge Management System

Web | Desktop Application

Name Knowledge Management System Technology PHP / Dot Net Category Web Application Description IEEE Paper No IEEE Paper Year - Contact Form [contact-form-7 id="71" title="Contact form 1"]

19Jul 2014 by chintan No Comments

View-invariant action recognition based on Artificial Neural Networks.

View-invariant action recognition based on Artificial Neural Networks. In this paper, a novel view invariant action recognition method based on neural network representation and recognition is proposed. The project has employed the technique mentioned and excellent results were obtained for a number of widely used font types. The technical approach followed in processing input images, detecting graphic symbols, analyzing and mapping the symbols and training the network for a set of desired Unicode characters corresponding to the input images are discussed in the subsequent sections. Even though the implementation might have some limitations in terms of functionality and robustness, the researcher is confident that it fully serves the purpose of addressing the desired objectives. The novel representation of action images is based on learning spatially related prototypes using Self Organizing…

19Jul 2014 by chintan

Lossless image compression based on data folding

Image Processing, Web | Desktop Application

Lossless image compression based on data folding The paper presents an approach for lossless image compression in spatial domain for continuous-tone images using a novel concept of image folding. The proposed method uses the property of adjacent neighbor redundancy for prediction. In this method, column folding followed by row folding is applied iteratively on the image till the image size reduces to a smaller pre-defined value. For column folding, elements of even columns are subtracted from elements of odd columns. Thereafter, row folding is applied on odd columns in a similar fashion. In row folding, even rows are subtracted from odd rows and the resultant odd rows are used for next iteration. The difference data, thus obtained, is stored in a tile format; which along with the reduced image is…

19Jul 2014 by chintan No Comments

A New Cell Counting Based Attack Against Tor.

A New Cell Counting Based Attack Against Tor. Various low-latency anonymous communication systems such as Tor and Anonymizer have been designed to provide anonymity service for users. In order to hide the communication of users, most of the anonymity systems pack the application data into equal-sized cells. Via extensive experiments on Tor, we found that the size of IP packets in the Tor network can be very dynamic because a cell is an application concept and the IP layer may repack cells. Based on this finding, we investigate a new cell-counting-based attack against Tor, which allows the attacker to confirm anonymous communication relationship among users very quickly. In this attack, by marginally varying the number of cells in the target traffic at the malicious exit onion router, the attacker can…

19Jul 2014 by chintan

A chaotic system based fragile watermarking scheme for image tamper detection

Image Processing, Web | Desktop Application

A chaotic system based fragile watermarking scheme for image tamper detection In the past few years, various fragile watermarking techniques have been proposed for image authen- tication and tamper detection. In this paper, a novel chaos based watermarking scheme for image authentication and tamper detection is proposed. Tamper localization and detection accuracy are two important aspects of the authentication watermarking schemes. Our scheme can detect any modifica- tion made to the image and can also indicate the specific locations that have been modified. To improve the security of the proposed scheme two chaotic maps are employed. Since chaotic maps are sensitive to initial values, the corresponding position relation between pixels in the watermarked image and the watermark get disturbed, which helps the watermarking scheme to withstand counterfeiting attacks. Initial values…

19Jul 2014 by chintan No Comments

Load Balancing Multipath Switching System with Flow Slice.

Load Balancing Multipath Switching System with Flow Slice. Multipath Switching systems are intensely used in state-of-the-art core routers to provide terabit or even petabit switching capacity. One of the most intractable issues in designing MPS is how to load balance traffic across its multiple paths while not disturbing the interflow packet orders. Previous packet-based solutions either suffer from delay penalties or lead to hardware complexity, hence do not scale. Flow-based hashing algorithms also perform badly due to the heavy-tailed flow-size distribution. In this paper, we develop a novel scheme, namely, Flow Slice that cuts off each flow into flow slices at every interflow interval larger than a slicing threshold and balances the load on a finer granularity. Based on the studies of tens of real Internet traces, we show that…

19Jul 2014 by chintan No Comments

Optimal Power Allocation in Multi-Relay MIMO Cooperative Networks: Theory and Algorithms.

Optimal Power Allocation in Multi-Relay MIMO Cooperative Networks: Theory and Algorithms. Cooperative networking is known to have significant potential in increasing network capacity and transmission reliability. Although there have been extensive studies on applying cooperative networking in multi-hop ad hoc networks, most works are limited to the basic three-node relay scheme and single-antenna systems. These two limitations are interconnected and both are due to a limited theoretical understanding of the optimal power allocation structure in MIMO cooperative networks (MIMO-CN). In this paper, we study the structural properties of the optimal power allocation in MIMOCN with per-node power constraints. More specifically, we show that the optimal power allocations at the source and each relay follow a matching structure in MIMO-CN. This result generalizes the power allocation result under the basic three-node…

19Jul 2014 by chintan

Linear distance coding for image classification

Image Processing, Web | Desktop Application

Linear distance coding for image classification The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC utilizes the locality constraints to project each descriptor into its local-coordinate system, and the projected coordinates are integrated by max pooling to generate the final representation. With linear classifier, the proposed approach performs remarkably better than the traditional nonlinear SPM, achieving state-of-the-art performance on several benchmarks. Compared with the sparse coding strategy [22], the objective function used by LLC has an analytical solution. In addition, the paper proposes a fast approximated LLC method by first performing a K-nearest-neighbor search and then solving a…

19Jul 2014 by chintan No Comments

Assessing the Veracity of Identity Assertions via OSNs.

Assessing the Veracity of Identity Assertions via OSNs. Anonymity is one of the main virtues of the Internet, as it protects privacy and enables users to express opinions more freely. However, anonymity hinders the assessment of the veracity of assertions that online users make about their identity attributes, such as age or profession. We propose FaceTrust, a system that uses online social networks to provide lightweight identity credentials while preserving a user’s anonymity. Face-Trust employs a game with a purpose” design to elicit the opinions of the friends of a user about the user’s self-claimed identity attributes, and uses attack-resistant trust inference to assign veracity scores to identity attribute assertions. FaceTrust provides credentials, which a user can use to corroborate his assertions. We evaluate our proposal using a live Facebook…

19Jul 2014 by chintan

Security Enhancement Scheme for Image Steganography using S-DES Technique

Image Processing

Security Enhancement Scheme for Image Steganography using S-DES Technique In today‟s information age, information sharing and transfer has increased exponentially. The information vulnerable to unauthorised access and interception, while in storage or transmission. Cryptography and Steganography are the two major techniques for secret communication. The contents of secret message are scrambled in cryptography, where as in steganography the secret message is embedded into the cover medium. This paper presents a new generalized model by combining cryptographic and steganographic Technique. These two techniques encrypt the data as well as hide the encrypted data in another medium so the fact that a message being sent is concealed. In cryptography we are using Simplified Data Encryption Standard (S-DES) algorithm to encrypt secret message and then alteration component method is used to hide encrypted…

19Jul 2014 by chintan

Robust Watermarking of Compressed and Encrypted JPEG2000 Images

Image Processing, Web | Desktop Application

Robust Watermarking of Compressed and Encrypted JPEG2000 Images Digital asset management systems (DAMS) generally handle media data in a compressed and encrypted form. It is sometimes necessary to watermark these compressed encrypted media items in the compressed-encrypted domain itself for tamper detection or ownership declaration or copyright management purposes. It is a challenge to watermark these compressed encrypted streams as the compression process would have packed the information of raw media into a low number of bits and encryption would have randomized the compressed bit stream. Attempting to watermark such a randomized bit stream can cause a dramatic degradation of the media quality. Thus it is necessary to choose an encryption scheme that is both secure and will allow watermarking in a predictable manner in the compressed encrypted domain. In…

19Jul 2014 by chintan

Image compression and decompression using adaptive interpolation

Image Processing, Web | Desktop Application

Image compression and decompression using adaptive interpolation A simple and fast lossy compression and decompression algorithm for digital images is proposed. The method offers varying compression ratios (depending on dimensions of the image) and the acquired decompressed image is close to the original one. A selectable tradeoff between storage size and image quality is allowed,making it possible to adjust degree of compression. Compared to JPEG, it provides us better compression ratio. The suggested method does not restrict itself to any particular type of image.

19Jul 2014 by chintan

A Query Formulation Language for the data web

A Query Formulation Language for the data web 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 also chose querying RDF, as it is the…

19Jul 2014 by chintan

Efficient and Discovery of Patterns in Sequence Data Sets.

Data mining, Web | Desktop Application

Efficient and Discovery of Patterns in Sequence Data Sets. 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 the pattern if it exists. Using both real…

19Jul 2014 by chintan No Comments

Denial of Service Defense through Web Referral

Denial of Service Defense through Web Referral The web is a complicated graph, with millions of websites interlinked together. In this paper, we propose to use this web sitegraph structure to mitigate flooding attacks on a website, using a new web referral architecture for privileged service (?WRAPS?). WRAPS allows a legitimate client to obtain a privilegeURL through a click on a referral hypherlink, from a website trusted by the target website. Using that URL, the client can get privileged access to the target website in a manner that is far less vulnerable to a DDoS flooding attack. WRAPS does not require changes to web client software and is extremely lightweight for referrer websites, which eases its deployment. The massive scale of the web sitegraph could deter attempts to isolate a…

16Jul 2014 by chintan

Mining Web Graphs for Recommendations.

Data mining, Web | Desktop Application

Mining Web Graphs for Recommendations. 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 Wide Web, including query suggestions, image recommendations,…

16Jul 2014 by chintan

Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques

Data mining, Web | Desktop Application

Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques 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.

16Jul 2014 by chintan

Predicting missing items in shopping cart using fast algorithm

Data mining, Web | Desktop Application

Predicting missing items in shopping cart using fast algorithm 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 rules generated form the basis for prediction. The…

16Jul 2014 by chintan

A Threshold-based Similarity Measure for Duplicate Detection

Data mining, Web | Desktop Application

A Threshold-based Similarity Measure for Duplicate Detection 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 into account both string and semantic similarity…

16Jul 2014 by chintan

Efficient Multi-dimensional Fuzzy Search for Personal Information Management Systems

Data mining, Web | Desktop Application

Efficient Multi-dimensional Fuzzy Search for Personal Information Management Systems 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 and algorithms to efficiently identify the most…

16Jul 2014 by chintan

Enabling Multilevel Trust in Privacy Preserving Data Mining

Data mining, Web | Desktop Application

Enabling Multilevel Trust in Privacy Preserving Data Mining 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 data through various means, and may combine…

16Jul 2014 by chintan

Advance Mining of Temporal High Utility Itemset

Data mining, Web | Desktop Application

Advance Mining of Temporal High Utility Itemset 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 of temporal high utility itemsets is an…

16Jul 2014 by chintan

A Framework for Personal Mobile Commerce Pattern Mining and Prediction

Data mining, Web | Desktop Application

A Framework for Personal Mobile Commerce Pattern Mining and Prediction 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 effectively and efficiently remove data points from…

16Jul 2014 by chintan

Investigation and Analysis of New Approach of Intelligent Semantic Web Search Engines

Data mining, Web | Desktop Application

Investigation and Analysis of New Approach of Intelligent Semantic Web Search Engines 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.

16Jul 2014 by chintan

Clustering Methods in Data Mining with its Applications in High Education

Data mining, Web | Desktop Application

Clustering Methods in Data Mining with its Applications in High Education 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 from the perspective of statistics, based on…

16Jul 2014 by chintan

A Novel Algorithm for Automatic Document Clustering

Data mining, Web | Desktop Application

A Novel Algorithm for Automatic Document Clustering 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 clustering. Existing partitioning algorithms have the limitation…

16Jul 2014 by chintan

Efficient Map/Reduce-based DBSCAN Algorithm with Optimized Data Partition

Name Efficient Map/Reduce-based DBSCAN Algorithm with Optimized Data Partition Technology .net Category Data Mining Description Place Description Here IEEE Paper Yes IEEE Paper Year 2013 Contact Form [contact-form-7 id="71" title="Contact form 1"]

16Jul 2014 by chintan

Dynamic Personalized Recommendation on Sparse Data

Data mining, Web | Desktop Application

Dynamic Personalized Recommendation on Sparse Data 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.

16Jul 2014 by chintan

Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases

Data mining, Web | Desktop Application

Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases 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. The information of high utility itemsets is…

16Jul 2014 by chintan

Sensitive Label Privacy Protection on Social Network Data

Data mining, Web | Desktop Application

Sensitive Label Privacy Protection on Social Network Data 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 that allow for graph data to be…

16Jul 2014 by chintan

Privacy against Aggregate Knowledge Attacks

Data mining, Web | Desktop Application

Privacy against Aggregate Knowledge Attacks 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 technique that generalizes attributes, only as much…

16Jul 2014 by chintan

Adapting a Ranking Model for Domain-Specific Search

Data mining, Web | Desktop Application

Adapting a Ranking Model for Domain-Specific Search 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 genre of content. a domain-specific ranking model…

16Jul 2014 by chintan

Efficient Similarity Search over Encrypted Data

Data mining, Web | Desktop Application

Efficient Similarity Search over Encrypted Data 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 for similarity tests, they are computationally intensive…

16Jul 2014 by chintan

Opinion Mining for web search

Data mining, Web | Desktop Application

Opinion Mining for web search 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 & web document frequency for mining the search…

16Jul 2014 by chintan

Distributed Association rule mining : Market basket Analysis

Distributed Association rule mining : Market basket Analysis 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.

16Jul 2014 by chintan

web usage mining using apriori

Data mining, Web | Desktop Application

web usage mining using apriori 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 files become a set of raw…

16Jul 2014 by chintan

Sales & Inventory Prediction using Data Mining

Data mining, Web | Desktop Application

Sales & Inventory Prediction using Data Mining 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.

16Jul 2014 by chintan

Hiding Sensitive Association Rule for Privacy Preservation

Data mining, Web | Desktop Application

Hiding Sensitive Association Rule for Privacy Preservation Data mining techniques have been widely used in various applications. However, the misuse of these techniques may lead to the disclosure of sensitive information. Researchers have recently made efforts at hiding sensitive association rules. Nevertheless, undesired side effects, e.g., non sensitive rules falsely hidden and spurious rules falsely generated, may be produced in the rule hiding process. In this paper, we present a novel approach that strategically modifies a few transactions in the transaction database to decrease the supports or confidences of sensitive rules without producing the side effects. Since the correlation among rules can make it impossible to achieve this goal, in this paper, we propose heuristic methods for increasing the number of hidden sensitive rules and reducing the number of modified…

16Jul 2014 by chintan

Efficiency of content distribution via network coding

Efficiency of content distribution via network coding Content distribution via network coding has received a lot of attention lately. However, direct application of network coding may be insecure. In particular, attackers can inject “bogus” data to corrupt the content distribution process so as to hinder the information dispersal or even deplete the network resource. Therefore, content verification is an important and practical issue when network coding is employed. When random linear network coding is used, it is infeasible for the source of the content to sign all the data, and hence, the traditional “hash-and-sign” methods are no longer applicable. Recently, a new on-the-fly verification technique has been proposed by Krohn et al. (IEEE S&P ’04), which employs a classical homomorphic hash function. However, this technique is difficult to be applied…

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