A Clustering Algorithm Considering Structural Relationships of Web Contents Kang Hyuncheol; Han Sang-Tae; Sun Young-Su;
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;