Visualization of navigation patterns on a Web site using model-based clustering
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Connectionist Approach for Website Visitors Behaviors Mining
AICCSA '01 Proceedings of the ACS/IEEE International Conference on Computer Systems and Applications
Visual Mining of Web Logs with DataTube2
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
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In this paper, we present two new approaches for the analysis of web site users behaviors. The first one is a synthetic visualization of Log file data and the second one is a coding of sequence based data. This coding allows us to carry out a vector quantization, and thus to find meaningful prototypes of the data set. For this, first the set of sessions is partitioned and then a prototype is extracted from each of the resulting classes. This analytic process allows us to categorize the different web site users behaviors interested by a set of categories of pages in a commercial site.