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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 | Source: | 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 | Keywords: | clustering; sequence analysis; web usage mining | Document URI: | http://hdl.handle.net/1942/2283 | ISSN: | 0219-1377 | e-ISSN: | 0219-3116 | DOI: | 10.1007/BF02637153 | ISI #: | 000226158800002 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2006 |
Appears in Collections: | Research publications |
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