Data Mining Algorithm of Browsing Pattern Based on Web Log

An Web log contains a large number of user browsing information, so how to effectively mine it for user browsing pattern is an important research subject. Based on the analysis of the problems in the current mining algorithm of the user browsing pattern, and combining the characteristics of the exis...

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Bibliographic Details
Published in2011 Fourth International Symposium on Knowledge Acquisition and Modeling pp. 307 - 311
Main Authors Li Yu-xia, Li Hong-yu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2011
Subjects
Algorithm design and analysis
Association rules
browsing pattern
incremental updating
Merging
Real time systems
temporal constraint
Transaction databases
Web log mining
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Summary:An Web log contains a large number of user browsing information, so how to effectively mine it for user browsing pattern is an important research subject. Based on the analysis of the problems in the current mining algorithm of the user browsing pattern, and combining the characteristics of the existing fast association rules mining algorithm, this paper adds the sequential constraint and the time factor, and puts forward a browsing pattern mining algorithm TBPM which is based on the temporal constraint. It also designs incremental updating algorithm based on the temporal frequent item set algorithm TBPM. At last, it makes a comparison with the related work of the class Apriori algorithm, and the experimental results on the actual data have verified the effectiveness of this algorithm.
ISBN:9781457717888
1457717883
DOI:10.1109/KAM.2011.88