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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2283

Title: Mining navigation patterns using a sequence alignment method
Authors: HAY, Birgit
WETS, Geert
VANHOOF, Koen
Issue Date: 2004
Publisher: SPRINGER LONDON LTD
Citation: KNOWLEDGE AND INFORMATION SYSTEMS, 6(2). p. 150-163
Abstract: In this article, a new method is illustrated for mining navigation patterns on a web site. Instead of clustering patterns by means of a Euclidean distance measure, in this approach users are partitioned into clusters using a non-Euclidean distance measure called the Sequence Alignment Method (SAM). This method partitions navigation patterns according to the order in which web pages are requested and handles the problem of clustering sequences of different lengths. The performance of the algorithm is compared with the results of a method based on Euclidean distance measures. SAM is validated by means of user-traffic data of two different web sites. Empirical results show that SAM identifies sequences with similar behavioral patterns not only with regard to content, but also considering the order of pages visited in a sequence.
Notes: Limburgs Univ Ctr, Fac Appl Econ Sci, B-3590 Diepenbeek, Belgium.Hay, B, Univ Limburg, Data Anal & Modelling Res Grp, Univ Campus,Gefouw D, B-3590 Diepenbeek, Belgium.birgit.hay@luc.ac.be
URI: http://hdl.handle.net/1942/2283
DOI: 10.1007/BF02637153
ISI #: 000226158800002
ISSN: 0219-1377
Category: A1
Type: Journal Contribution
Validation: ecoom, 2006
Appears in Collections: Research publications

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