International Journal of Web Science (6 papers in press)
Web Documents Semantic Similarity by extending Document Ontology Using Current Trends
by Poonam Chahal, Manjeet Singh, Suresh Kumar
Abstract: Semantic evaluation of similarity index is computation of relatedness between terms/concepts/documents. In this paper we have given a novel semantic similarity approach to overcome the limitations that exists in calculating semantic similarity score. In our approach we are extracting words/terms from the set of documents, and then replacing the extracted words/terms by their respective set of probable concepts stored in a dictionary. The concepts retrieved from the dictionary are connected using relationships from a base ontology for construction of document ontology corresponding to a given document. The ontology constructed this way is further extended using trend relationships stored in a separate database. Finally, the extended documents ontologys are compared for finding the relatedness between the documents. It is proved empirically that the proposed approach gives the better results of semantic similarity as compared with the conventional approaches.
Keywords: Semantic Web; Concepts; Ontology; Semantic; Similarity; Document Ontology; Words; Syntactic Analysis; Parsing; Web Page.
Comparative Analysis of Web Development Languages Performances
by Chibuzo Onyemaobi, Ifeyinwa Ajah
Abstract: Web programming languages employed by students, teachers and professionals have been redesigned and upgraded rapidly by the developers and Interest Companies. This paper uses content analysis method to compare various web development languages. The comparison is based on their web security, web development, web services, object oriented programming (OOP) base abstraction and user interface design. A view of the capabilities of each of these languages is clinically presented, and should help those trying to understand their technical similarities, differences, and capabilities.
Keywords: RIAs; Web Development Languages; Web Services; Web User Interface; API.
Term Co-occurrence and Context Window based Combined Approach for Query Expansion with the Semantic Notion of Terms
by Jagendra Singh, Aditi Sharan
Abstract: Query expansion is a well known method for improving the performance of information retrieval systems. Pseudo Relevance feedback (PRF) based query expansion is a type of query expansion approach that assumes the top ranked retrieved documents are relevant. But this assumption is not always true; it may also possible that a PRF document may contain different topics, which may or may not be relevant to the query terms even if the documents are judged relevant. In this paper our focus is to capture the limitations of PRF based query expansion and propose a hybrid method to improve the performance of PRF based query expansion by combining corpus based term co-occurrence information, context window of query terms and semantic information of term. Firstly, the paper suggest use of various corpus based term co-occurrence approach to select an optimal combination of query terms from a pool of terms obtained using PRF based query expansion. Third, we use semantic similarity approach to rank the query expansion terms obtained from top feedback documents. Fourth, we combine co-occurrence, context window and semantic similarity based approaches together to select the best expansion for query reformulation. The experiments were performed on FIRE ad-hoc and TREC-3 benchmark datasets of information retrieval task. The results show significant improvement in terms of precision, recall and mean average precision (MAP). This experiments shows that the combination of various techniques in an intelligent way gives us goodness of all of them. As this is the first attempt in this direction there is a large scope of improving these techniques.
Keywords: Information retrieval; Query expansion; Pseudo-relevant feedback; Term co-occurrence; Term context window; Semantic similarity; WordNet.
Pseudo Relevance Feedback based on Majority Voting Mechanism
by Mawloud Mosbah, Bachir Boucheham
Abstract: Pseudo-relevance feedback mechanism has come to improve the performance of CBIR rnsystems before visualizing the final results and without any user assistance. In this paper, we show the superiority of our proposed Pseudo-relevance feedback scheme Majority Voting Algorithm. We specifically compare our proposition to two published and known clustering methods: HACM and K-means and also to some pseudo relevance feedback methods: Pseudo Query Point Movement, Pseudo Standard Rocchio Formula and Pseudo Adaptive Shifting Query. Experiments are conducted on the heterogeneous Wang (COREL1K) database, Google Image engine, and color moments as a signature. The obtained results show the clear superiority of our proposed algorithm in terms of effectiveness and enable us to compare the rnconsidered methods of the literature.
Keywords: CBIR; Re-ranking; Pseudo relevance feedback; Majority voting re-ranking algorithm; HACM; K-means; Precision; Recall.
Creating Web Signature for Each Individual User and Its Various Applications
by Rozita Jamili Oskouei
Abstract: In this paper we describe our experiments and their results to generate unique Web signature for students with exploring proxy servers access log files for varying periods from 15 to 90 continuous days and study its relationships with their time spent on Internet , academic performance and participating in curricular activities . Further, we demonstrate the usage of this Web signature to identify outliers in student community based on their different behavioral dimensions. k-means and DBSCAN clustering methods are used to identify outliers in student community on the basis of time spent, CPI, and Signature length. Our results contradicts widely held perception that access and usage of Internet have adverse effects on academic performance. It seems to contribute positively in academic performance. The major applications of Web-signature are:rn Help to administrators for predicting the more overload timing per day and plan for that. rn Grouping users based on their similarity of contents of Web-Signatures and establishing social network between those users based on their similar behaviors. There are several benefits for creating this social network, such as: rno Help to fresher students for connecting to professional and expert people who are working in similar domains and discuss about problems or difficulties especially in educational environments. In fast one of the main usage of the Web Signature would be creating a social network between different students in all around the world based on their similarity of interests or behaviors in Internet for exchanging knowledge with together.
Keywords: Web Signature; Access log files; Academic performance; outliers detection; Behavior mining.
Mitigation of SQL Injection Vulnerability during Development of Web Applications
by Navdeep Kaur, Parminder Kaur
Abstract: SQL Injection (SQLI) attack is consistently proliferating across the globe. According to Open Web Application Security Project (OWASP) Top Ten Cheat Sheet-2014, SQLI is at top in the list of online attacks. The cause of spread of SQLI is thought to be Unsecure Software Engineering. The Software Development process itself appears to look at security as an add-on to be checked and deployed towards the end of the software development lifecycle (SDLC) which leads to vulnerabilities in web applications. This paper is an attempt to integrate security during development of web application. The paper introduces a grounds-up approach for developing SQLI free web application. The process of occurrence of SQLI attack is discussed with the help of suitable example. Various security activities desired to mitigate SQLI during Software Development Life Cycle are discussed.
Keywords: SQL Injection,SQLI; Software Security; Software Development Lifecycle; Threat Modeling; Security Requirements.