Implementation of an Efficient Matrix based Algorithm for Clustering in Web Usage Mining
Journal Title: International Journal of Computational Engineering and Management IJCEM - Year 2012, Vol 15, Issue 4
Abstract
Usage patterns discovered through Web usage mining are effective in capturing item-to-item and user-to-user relationships and similarities at the level of user sessions. However, without the benefit of deeper domain knowledge, such patterns provide little insight into the underlying reasons for which such items or users are grouped together. Furthermore, the inherent and increasing heterogeneity of the Web has required Web-based applications to more effectively integrate a variety of types of data across multiple channels and from different sources. Thus, a focus on techniques and architectures for more effective integration and mining of content, usage, and structure data from different sources is likely to lead to the next generation of more useful and more intelligent applications, and more sophisticated tools for Web usage mining that can derive intelligence from user transactions on the Web. This paper gives an insight into the proposed MABAC Algorithm and the implementation to show how it provides useful information within clusters.
Authors and Affiliations
Kanika Gupta, Kirti Aggarwal and Neha Aggarwal
Keywords
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