Segmentation of visiting patterns on web sites using a sequence alignment method

Empirical results show that SAM identifies segments presenting behavioral characteristics not only with regard to content but also considering the order of pages that are visited on a web site.

Abstract

In this article, a new method is illustrated for segmentation of visiting patterns on a web site. Instead of clustering users by means of a Euclidean distance measure, in our approach users are partitioned into clusters using a non-Euclidean distance measure, called Sequence Alignment Method (SAM). This method ensures that sequential relationships, represented by the order of elements, are taken into account. In experiments using real traffic data on the web site of a Belgian telecom provider, the performance of SAM is compared with the results of a method based on Euclidean distance measures. Empirical results show that SAM identifies segments presenting behavioral characteristics not only with regard to content but also considering the order of pages that are visited on a web site.