Using information filtering in Web data mining process

Xujuan Zhou, Yuefeng Li, Peter Bruza, Sheng-Tang Wu, Yue Xu, Raymond Y. K. Lau

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

10 Citations (Scopus)


The amount of Web information is growing rapidly, improving the efficiency and accuracy of Web information retrieval is uphill battle. There are two fundamental issues regarding the effectiveness of Web information gathering: information mismatch and overload. To tackle these difficult issues, an integrated information filtering and sophisticated data processing model has been presented in this paper. In the first phase of the proposed scheme, an information filter that based on user search intents was incorporated in Web search process to quickly filter out irrelevant data. In the second data processing phase, a pattern taxonomy model (PTM) was carried out using the reduced data. PTM rationalizes the data relevance by applying data mining techniques that involves more rigorous computations. Several experiments have been conducted and the results show that more effective and efficient access Web information has been achieved using the new scheme.
Original languageEnglish
Title of host publicationProceedings of the IEEE/WIC/ACM international conference on web intelligence (WI 2007)
EditorsTsau Young Lin, Laura Haas, Janusz Kacprzyk, Rajeev Motwani, Andrei Broder, Howard Ho
Place of PublicationSilicon Valley, CA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages7
ISBN (Print)9780769530260
Publication statusPublished - 2007
Externally publishedYes
EventIEEE/WIC/ACM international conference on web intelligence - Silicon Valley, CA
Duration: 2 Nov 20075 Nov 2007


ConferenceIEEE/WIC/ACM international conference on web intelligence
CitySilicon Valley, CA


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