Data Mining Approach To Analyze Virtual Museums Web Log Data

Abstract

Virtual museums are part of digital libraries with large collections of multi dimensional data. Knowledge engineering tools facilitate extraction of meaningful information to support data mining features such as classification, decision making, associations, clustering and ranking. In this paper we analyzed raw web log data gathered from online virtual museum server. We applied knowledge engineering techniques on this log data to discover some interesting patterns from user sessions. We also performed mining on web log data for collection ranking, association rule mining and decision trees construction. These details improved the organization of virtual museums.

Authors and Affiliations

Mr. B. V. RamaKrishna, Dr. K. V. V. S. Narayana Murthy

Keywords

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  • EP ID EP28222
  • DOI -
  • Views 284
  • Downloads 3

How To Cite

Mr. B. V. RamaKrishna, Dr. K. V. V. S. Narayana Murthy (2015). Data Mining Approach To Analyze Virtual Museums Web Log Data. International Journal of Research in Computer and Communication Technology, 4(8), -. https://europub.co.uk/articles/-A-28222