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A Clustering Algorithm Considering Structural Relationships of Web Contents
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 Title & Authors
A Clustering Algorithm Considering Structural Relationships of Web Contents
Kang Hyuncheol; Han Sang-Tae; Sun Young-Su;
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Application of data mining techniques to the world wide web, referred to as web mining, has been the focus of several recent researches. With the explosive growth of information sources available on the world wide web, it has become increasingly necessary to track and analyze their usage patterns. In this study, we introduce a process of pre-processing and cluster analysis on web log data and suggest a distance measure considering the structural relationships between web contents. Also, we illustrate some real examples of cluster analysis for web log data and look into practical application of web usage mining for eCRM.
Web Mining;Web Log;Cluster Analysis;Similarity;Distance Measure;
 Cited by
사용자 웹 사이트 방문 시간을 고려한 연관 규칙,강형창;김철수;이동철;

산업경영시스템학회지, 2006. vol.29. 2, pp.104-109
아이템 사용시간을 고려한 Apriori알고리즘,강형창;양근탁;김철수;이윤정;이봉규;

전기학회논문지, 2010. vol.59. 7, pp.1327-1331 crossref(new window)
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