Automatic Pattern-Taxonomy Extraction for Web Mining

Authors:
Sheng-Tang Wu;Yuefeng Li;Yue Xu;Binh Pham;Phoebe Chen
Affiliations:
Queensland University of Technology, Australia;Queensland University of Technology, Australia;Queensland University of Technology, Australia;Queensland University of Technology, Australia;Deakin University, Australia
Venue:
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Year:
2004

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Abstract

In this paper, we propose a model for discovering frequent sequential patterns, phrases, which can be used as profile descriptors of documents. It is indubitable that we can obtain numerous phrases using data mining algorithms. However, it is difficult to use these phrases effectively for answering what users want. Therefore, we present a pattern taxonomy extraction model which performs the task of extracting descriptive frequent sequential patterns by pruning the meaningless ones. The model then is extended and tested by applying it to the information filtering system. The results of the experiment show that pattern-based methods outperform the keyword-based methods. The results also indicate that removal of meaningless patterns not only reduces the cost of computation but also improves the effectiveness of the system.