A study on the mining access patterns from web log data

Jeong Yong Ahn

A study on the mining access patterns from web log data

Jeong Yong Ahn^*

^*Corresponding author for this work

Department of Statistics

Seonam University

Research output: Contribution to journal › Letter › peer-review

1 Scopus citations

Abstract

Nowadays, the World Wide Web is continuing to expand at an amazing rate as a medium for conducting business in addition to disseminating information, and Web users are remarkably increasing. Human activities in virtual space as the Web are producing large volumes of data, and Web data mining to extract information from Web data has become an important research area. In this paper, we examine the features of Web log data and propose a method for transaction identification. We also introduce a new problem of user segmentation and present a method for solving this problem.

Original language	English
Pages (from-to)	782-785
Number of pages	4
Journal	IEICE Transactions on Information and Systems
Volume	E85-D
Issue number	4
State	Published - 2002.04

Keywords

Discovering visiting patterns
Transaction identification
User segmentation
Web data mining

Cite this

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AB - Nowadays, the World Wide Web is continuing to expand at an amazing rate as a medium for conducting business in addition to disseminating information, and Web users are remarkably increasing. Human activities in virtual space as the Web are producing large volumes of data, and Web data mining to extract information from Web data has become an important research area. In this paper, we examine the features of Web log data and propose a method for transaction identification. We also introduce a new problem of user segmentation and present a method for solving this problem.

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KW - Transaction identification

KW - User segmentation

KW - Web data mining

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A study on the mining access patterns from web log data

Abstract

Keywords

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