Using Web clustering for Web communities mining and analysis

Yanchun ZHANG, Guandong XU

Research output: Chapter in Book/Report/Conference proceedingChapters

7 Citations (Scopus)

Abstract

Due to the inherent correlation among Web objects and the lack of a uniform schema of web documents, Web community mining and analysis has become an important area for Web data management and analysis. The research of Web communities spans a number of research domains such as Web mining, Web search, clustering and text retrieval. In this talk we will present some recent studies on this topic, which cover finding relevant Web pages based on linkage information, discovering user access patterns through analyzing Web log files, co-clustering Web objects and investigating social networks from Web data. The algorithmic issues and related experimental studies will be addressed. Some research directions are also to be discussed. Copyright © 2008 IEEE.

Original languageEnglish
Title of host publicationProceedings of 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
Place of PublicationUSA
PublisherIEEE
Pages20-31
ISBN (Print)9780769534961
DOIs
Publication statusPublished - 2008

Citation

Zhang, Y., & Xu, G. (2008). Using Web clustering for Web communities mining and analysis. In Proceedings of 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008 (pp. 20-31). IEEE. https://doi.org/10.1109/WIIAT.2008.415

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