@article{MAKHILLIJSC201712321408,
    title = {Proposed Partitioning Approach and Hierarchical Approach for the
Clustering of Web Users},
    journal = {International Journal of Soft Computing},
    volume = {12},
    number = {3},
    pages = {156-163},
    year = {2017},
    issn = {1816-9503},
    doi = {ijscomp.2017.156.163},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2017.156.163},
    author = {Hadj- and},
    keywords = {Web usage mining,clustering partitioning approach,clustering hierarchical agglomerative,k-medoids algorithm,evaluation measures of clusters,rulesquality measures},
    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.}
    }