Algorithms for clustering data
Algorithms for clustering data
Recent trends in hierarchic document clustering: a critical review
Information Processing and Management: an International Journal
Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Information Retrieval
Text Mining: Predictive Methods for Analyzing Unstructured Information
Text Mining: Predictive Methods for Analyzing Unstructured Information
A Framework for Automatic Topic Discovery on subWebs
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02
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As the amount of available information on the Internet grows, it is becoming increasingly difficult for users to find information that is relevant to their needs. Against this backdrop, a need for an automated tool that can find information quickly and easily has surfaced. In this paper, we propose a Clustering Framework for crawling and clustering the necessary information from Web pages. The proposed clustering framework consists of three modules: a preprocessing module, clustering module and community module. Using this framework, we are able to automatically cluster Web pages according to topic and rank them in terms of relevance. We describe this framework, and show the results of our preliminary validation work.