Mining Navigation Patterns Using a Sequence Alignment Method

• Published in: Knowledge and information systems Vol. 6; no. 2; pp. 150 - 163
• Main Authors: Hay, Birgit, Wets, Geert, Vanhoof, Koen
• Format: Journal Article
• Language: English
• Published: London Springer Nature B.V 01-03-2004
• Subjects: Algorithms; Clustering; Customization; Websites
• ISSN: 0219-1377; 0219-3116
• DOI: 10.1007/s10115-003-0109-6

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.