Inferring Web communities from link topology
Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems: links, objects, time and space---structure in hypermedia systems
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Efficient identification of Web communities
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Creating a Web community chart for navigating related communities
Proceedings of the 12th ACM conference on Hypertext and Hypermedia
Proceedings of the 11th international conference on World Wide Web
Finding a Web Community by Maximum Flow Algorithm with HITS Score Based Capacity
DASFAA '03 Proceedings of the Eighth International Conference on Database Systems for Advanced Applications
Web Communities: Models and Algorithms
World Wide Web
Finding similar academic web sites with links, bibliometric couplings and colinks
Information Processing and Management: an International Journal
Visualizing linguistic and cultural differences using Web co-link data: Research Articles
Journal of the American Society for Information Science and Technology
UK academic web links and collaboration - an exploratory study
Journal of Information Science
Visualization of the Nordic academic web: Link analysis using social network tools
Information Processing and Management: an International Journal
Visualization of the Chinese academic web based on social network analysis
Journal of Information Science
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The World Wide Web has become an important source of academic information. The linking feature of the Web has been used to study the structure of academic web, as well as the presence of academic and research institutes on the Web. In this paper, we propose an integrated model for exploring the subject macrostructure of a specific academic topic on the Web and automatically depicting the knowledge map that is closer to what a domain expert would expect. The model integrates a hyperlink-induced topic search (HITS)-based link network extending strategy and a semantic based clustering algorithm with the aid of co-link analysis and social network analysis (SNA) to discover subject-based communities in the academic web space. We selected to use websites as analytical units rather than web pages because of the subject stability of a website. Compared with traditional techniques in Webometrics and SNA that have been used for such analyses, our model has the advantages of working on open web space (capability to explore unknown web resources and identify important ones) and of automatically building an extendable and hierarchical web knowledge map. The experiment in the area of Information Retrieval shows the effectiveness of the integrated model in analyzing and portraying of subject clustering phenomenon in academic web space.