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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2816

Title: Discovering interesting navigations on a web site using SAM
Authors: HAY, Birgit
WETS, Geert
VANHOOF, Koen
Issue Date: 2005
Publisher: SPRINGER-VERLAG BERLIN
Citation: INTELLIGENT TECHNIQUES FOR WEB PERSONALIZATION. p. 187-200
Series/Report: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, 3169
Abstract: In this article, a new algorithm called Sequence Alignment Method extended with an Interestingness Measure (SAM(I)) is illustrated for mining navigation patterns on a web site. Through log file analysis, SAMI distinguishes interesting patterns (i.e. unexpected, surprising patterns contradicting with the structure of the web site or direct hyperlinks between web pages) from uninteresting patterns (i.e. expected, known, obvious patterns resulting from the structure of the web site or direct hyperlinks between web pages) and provides information about the order of visited web pages. The algorithm is validated using real data sets of the Music Machines web site http://machines.hyperreal.org, home of musical electronics on the web. Empirical results show that SAMI identifies profiles of visiting behavior, which may be used for web personalization techniques and for optimizing the layout of the web site through structuring of page-links.
Notes: Limburgs Univ Ctr, Fac Appl Econ Sci, B-3590 Diepenbeek, Belgium.Hay, B, Limburgs Univ Ctr, Fac Appl Econ Sci, B-3590 Diepenbeek, Belgium.birgit.hay@luc.ac.be geert.wets@luc.ac.be koen.vanhoof@luc.ac.be
URI: http://hdl.handle.net/1942/2816
DOI: 10.1007/11577935
ISI #: 000233848300010
ISSN: 0302-9743
Category: A1
Type: Journal Contribution
Validation: ecoom, 2007
Appears in Collections: Research publications

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