Pattern taxonomy mining for information filtering

Xujuan Zhou, Yuefeng Li, Peter Bruza, Yue Xu, Raymond Y. K. Lau

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2 Citations (Scopus)

Abstract

This paper examines a new approach to information filtering by using data mining method. This new model consists of two components, namely, topic filtering and pattern taxonomy mining. The aim of using topic filtering is to quickly filter out irrelevant information based on the user profiles. The aim of applying pattern taxonomy mining techniques is to rationalize the data relevance on the reduced data set. Our experiments on Reuters RCV1(Reuters Corpus Volume 1) data collection show that more effective and efficient information access has been achieved by combining the strength of information filtering and data mining method.
Original languageEnglish
Title of host publicationAI 2008
Subtitle of host publicationAdvances in Artificial Intelligence : 21st Australasian Joint Conference on Artificial Intelligence. Proceedings
EditorsWayne Wobcke, Mengjie Zhang
Place of PublicationBerlin Heidelberg
PublisherSpringer, Springer Nature
Pages416-422
Number of pages7
ISBN (Print)9783540893776
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventAustralasian Joint Conference on Artificial Intelligence (21st : 2008) - Auckland, New Zealand
Duration: 1 Dec 20085 Dec 2008

Publication series

NameLecture notes in computer science
PublisherSpringer
Volume5360
ISSN (Print)0302-9743

Conference

ConferenceAustralasian Joint Conference on Artificial Intelligence (21st : 2008)
CityAuckland, New Zealand
Period1/12/085/12/08

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