Title :
A probabilistic validation algorithm for Web users´ clusters
Author :
Pallis, George ; Angelis, Lefteris ; Vakali, Athena ; Pokorny, Jaroslav
Author_Institution :
Dept. of Informatics, Aristotle Univ., Thessaloniki, Greece
Abstract :
Cluster analysis is one of the most important aspects in the data mining process for discovering groups and identifying interesting distributions or patterns over the considered data sets. In the context of Web data mining, model-based clustering algorithms are often used to cluster similar users´ sessions in order to determine Website access behaviors. An important issue in cluster analysis is the evaluation of clustering results to find the partitioning that best fits the underlying data. In this paper, we present a novel validation technique for model based clustering approaches.
Keywords :
Internet; data mining; pattern clustering; probability; Web users clusters; data mining process; model-based clustering algorithms; novel validation technique; probabilistic validation algorithm; Clustering algorithms; Context modeling; Data mining; Informatics; Mathematics; Navigation; Partitioning algorithms; Search engines; Web mining; Web pages;
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
Print_ISBN :
0-7803-8566-7
DOI :
10.1109/ICSMC.2004.1401178