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A Clustering Algorithm for Sequence Data Using Rough Set Theory
Journal of The Korea Society of Computer and Information
Abbr :
JKSCI
2008, 13(2), pp.113-120
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science
2008, 13(2), pp.113-120
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science
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The World Wide Web is a dynamic collection of pages that includes a huge number of hyperlinks and huge volumes of usage informations. The resulting growth in online information combined with the almost unstructured web data necessitates the development of powerful web data mining tools. Recently, a number of approaches have been developed for dealing with specific aspects of web usage mining for the purpose of automatically discovering user profiles. We analyze sequence data, such as web-logs, protein sequences, and retail transactions. In our approach, we propose the clustering algorithm for sequence data using rough set theory. We present a simple example and experimental results using a splice dataset and synthetic datasets.
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