Combining the web content and usage mining to understand the visitor behavior in a web site

I
ICDM
2003
Third IEEE International Conference on Data Mining (ICDM'03)
Abstract - Combining the web content and usage mining to understand the visitor behavior in a web site

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Third IEEE International Conference on Data Mining (ICDM'03)

Melbourne, Florida

November 19-November 22

ISBN: 0-7695-1978-4

	ASCII Text	x
	Juan Vel?squez, Hiroshi Yasuda, Terumasa Aoki, "Combining the web content and usage mining to understand the visitor behavior in a web site," Data Mining, IEEE International Conference on, pp. 669, Third IEEE International Conference on Data Mining (ICDM'03), 2003.

	BibTex	x
	@article{ 10.1109/ICDM.2003.1251004, author = {Juan Vel?squez and Hiroshi Yasuda and Terumasa Aoki}, title = {Combining the web content and usage mining to understand the visitor behavior in a web site}, journal ={Data Mining, IEEE International Conference on}, volume = {0}, year = {2003}, isbn = {0-7695-1978-4}, pages = {669}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1251004}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining, IEEE International Conference on TI - Combining the web content and usage mining to understand the visitor behavior in a web site SN - 0-7695-1978-4 SP EP A1 - Juan Vel?squez, A1 - Hiroshi Yasuda, A1 - Terumasa Aoki, PY - 2003 KW - null VL - 0 JA - Data Mining, IEEE International Conference on ER -

Juan Vel?squez, University of Tokyo, Japan

Hiroshi Yasuda, University of Tokyo, Japan

Terumasa Aoki, University of Tokyo, Japan

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1251004

A web site is a semi structured collection of different kinds of data, whose motivation is show relevant information to visitor and by this way capture her/his attention.

Understand the specifics preferences that define the visitor behavior in a web site, is a complex task. An approximation is suppose that it depend the content, navigation sequence and time spent in each page visited. These variables can be extracted from the web log files and the web site itself, using web usage and content mining respectively. Combining the describe variables, a similarity measure among visitor sessions is introduced and used in a clustering algorithm, which identifies groups of similar sessions, allowing the analysis of visitors behavior.

In order to prove the methodology's effectiveness, it was applied in a certain web site, showing the benefits of the described approach.

Citation:

Juan Vel?squez, Hiroshi Yasuda, Terumasa Aoki, "Combining the web content and usage mining to understand the visitor behavior in a web site," icdm, pp.669, Third IEEE International Conference on Data Mining (ICDM'03), 2003

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