Following the approach described by Heckerman et al. ([5]), we present an application of Dependency Networks and Bayesian Networks to the analysis of a clickstream data set. Our target is to discover which paths are more often followed by the users. The relation between one web page and another one is represent by a direct graph. Whereas Bayesian Networks use direct acyclic graphs, Dependency Networks may contain cyclic structures. The analysis will be performed with the WinMine Toolkit software.
Dependency Networks And Bayesian Networks For Web Mining / C. Tarantola, E. Blanc - In: Data Mining III / [a cura di] A. Zanasi, C.A. Brebbia, N.F.F. Ebecken, P. Melli. - [s.l] : WIT Press, 2002. - ISBN 1-85312-925-9. - pp. 947-954
Dependency Networks And Bayesian Networks For Web Mining
C. Tarantola
;
2002
Abstract
Following the approach described by Heckerman et al. ([5]), we present an application of Dependency Networks and Bayesian Networks to the analysis of a clickstream data set. Our target is to discover which paths are more often followed by the users. The relation between one web page and another one is represent by a direct graph. Whereas Bayesian Networks use direct acyclic graphs, Dependency Networks may contain cyclic structures. The analysis will be performed with the WinMine Toolkit software.
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