Authors : Hadj- Tayeb Karima and Belbachir Hafida
Abstract: In web usage mining, the cluster analysis is the most important technical. Based on this technical, the users groups provide insight into browsers behavior to refine the behavioral patterns to the website access and to identify frequently visited pages. Into the clustering context, the most popular approach is the partitioning approach but itprinciple as it stands seems inappropriate on sequential data. This work attempts to over come limitations and proposes a new model of users clustering. This approach is based on set ofmeasures which ensure rules quality and evaluate the interest of generated sequential rules. The experimental study implements the proposed algorithm, the k-medoids algorithm and hierarchical agglomerative approach in order to guarantee the good partitioning of the data interms of evaluation measures of the clustering quality and calculation time. Relative result sattempt to ensure a good partitioning data in terms of evaluation measures of clustering quality.
Hadj- Tayeb Karima and Belbachir Hafida, 2017. Proposed Partitioning Approach and Hierarchical Approach for the Clustering of Web Users. International Journal of Soft Computing, 12: 156-163.