A New Similarity Measure to Understand Visitor Behavior in a Web Site

Juan D. Velásquez, Hiroshi Yasuda, Terumasa Aoki, Richard Weber

Research output: Contribution to journal › Article

32 Citations (Scopus)

Abstract

The behavior of visitors browsing in a web site offers a lot of information about their requirements and the way they use the respective site. Analyzing such behavior can provide the necessary information in order to improve the web site's structure. The literature contains already several suggestions on how to characterize web site usage and to identify the respective visitor requirements based on clustering of visitor sessions. Here we propose to combine visitor behavior with the content of the respective web pages and the similarity between different page sequences in order to define a similarity measure between different visits. This similarity serves as input for clustering of visitor sessions. The application of our approach to a bank's web site and its visitor sessions shows its potential for internet-based businesses.

Original languageEnglish
Pages (from-to)389-396
Number of pages8
JournalIEICE Transactions on Information and Systems
VolumeE87-D
Issue number2
Publication statusPublished - 2004 Feb

Keywords

  • Browsing behavior
  • Clustering
  • Similarity measure
  • Web mining

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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    Velásquez, J. D., Yasuda, H., Aoki, T., & Weber, R. (2004). A New Similarity Measure to Understand Visitor Behavior in a Web Site. IEICE Transactions on Information and Systems, E87-D(2), 389-396.