TY  - JOUR
T1  - Proposed Partitioning Approach and Hierarchical Approach for the
Clustering of Web Users
AU - Tayeb Karima, Hadj- AU - Hafida, Belbachir 
JO  - International Journal of Soft Computing
VL  - 12
IS  - 3
SP  - 156
EP  - 163
PY  - 2017
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2017.156.163
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2017.156.163
KW  - Web usage mining
KW  -clustering partitioning approach
KW  -clustering hierarchical agglomerative
KW  -k-medoids algorithm
KW  -evaluation measures of clusters
KW  -rulesquality measures
AB  - 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.
ER  -