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Pattern taxonomy mining for information filtering

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

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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. © 2008 Springer Berlin Heidelberg.
Original languageEnglish
Title of host publicationAI 2008: Advances in Artificial Intelligence
Subtitle of host publication21st Australasian Joint Conference on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Pages416-422
Volume5360 LNAI
ISBN (Print)3540893776, 9783540893776
DOIs
Publication statusPublished - 2008
Event21st Australasian Joint Conference on Artificial Intelligence, AI 2008 - Auckland, New Zealand
Duration: 1 Dec 20085 Dec 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5360 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st Australasian Joint Conference on Artificial Intelligence, AI 2008
PlaceNew Zealand
CityAuckland
Period1/12/085/12/08

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