Grouping Web page references into transactions for mining World Wide Web browsing patterns

R. Cooley, B. Mobasher, J. Srivastava

Research output: Contribution to conferencePaper

63 Citations (Scopus)

Abstract

Web-based organizations often generate and collect large volumes of data in their daily operations. Analyzing such data involves the discovery of meaningful relationships from a large collection of primarily unstructured data, often stored in Web server access logs. While traditional domains for data mining, such as point of sale databases, have naturally defined transactions, there is no convenient method of clustering web references into transactions. This paper identifies a model of user browsing behavior that separates web page references into those made for navigation purposes and those for information content purposes. A transaction identification method based on the browsing model is defined and successfully tested against other methods, such as the maximal forward reference algorithm proposed in [1]. Transactions identified by the proposed methods are used to discover association rules from real world data using the WEBMINER system.

Original languageEnglish
Pages2-9
Number of pages8
Publication statusPublished - 1 Dec 1997
EventProceedings of the 1997 IEEE Knowledge & Data Engineering Exchange Workshop, KDEX - Newport Beach, CA, USA
Duration: 4 Nov 19974 Nov 1997

Other

OtherProceedings of the 1997 IEEE Knowledge & Data Engineering Exchange Workshop, KDEX
CityNewport Beach, CA, USA
Period4/11/974/11/97

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Cooley, R., Mobasher, B., & Srivastava, J. (1997). Grouping Web page references into transactions for mining World Wide Web browsing patterns. 2-9. Paper presented at Proceedings of the 1997 IEEE Knowledge & Data Engineering Exchange Workshop, KDEX, Newport Beach, CA, USA, .