Discovering web access patterns and trends by applying OLAP and data mining technology on web logs

Osmar R. Zaiane, Man Xin, Jiawei Han

Research output: Contribution to conferencePaper

Abstract

As a confluence of data mining and WWW technologies, it is now possible to perform data mining on web log records collected from the Internet web page access history. The behaviour of the web page readers is imprinted in the web server log files. Analyzing and exploring regularities in this behaviour can improve system performance, enhance the quality and delivery of Internet information services to the end user, and identify population of potential customers for electronic commerce. Thus, by observing people using collections of data, data mining can bring considerable contribution to digital library designers. In a joint effort between the TeleLearning-NCE project on Virtual University and NCE-IRIS project on data mining, we have been developing the knowledge discovery tool, WebLogMiner, for mining web server log files. This paper presents the design of the WebLogMiner, reports the current progress, and outlines the future work in this direction.

Original languageEnglish (US)
Pages19-29
Number of pages11
StatePublished - Jan 1 1998
Externally publishedYes
EventProceedings of the 1998 IEEE Forum on Research and Technology Advances in Digital Libraries, IEEE ADL'98 - Santa Barbara, CA, USA
Duration: Apr 22 1998Apr 24 1998

Other

OtherProceedings of the 1998 IEEE Forum on Research and Technology Advances in Digital Libraries, IEEE ADL'98
CitySanta Barbara, CA, USA
Period4/22/984/24/98

ASJC Scopus subject areas

  • Management of Technology and Innovation

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    Zaiane, O. R., Xin, M., & Han, J. (1998). Discovering web access patterns and trends by applying OLAP and data mining technology on web logs. 19-29. Paper presented at Proceedings of the 1998 IEEE Forum on Research and Technology Advances in Digital Libraries, IEEE ADL'98, Santa Barbara, CA, USA, .