Biclustering of Web Usage Data

by Rathipriya
(India)

Original Text: Biclustering of Web Usage Data

Biclustering has the potential to make significant contributions in the field of information retrieval and web mining etc. The objective of this paper is to analyze the complex association between users and pages of a web site by using biclustering algorithm. This method can automatically identify the groups of users that show similar expression patterns under a specific subset of the pages. This paper presents a hybrid binary particle swarm optimization with genetic mutation method for biclustering algorithm. It detects the user profile group according to their coherent browsing behavior. The interpretation of this biclustering results is useful for marketing and sales strategies. The results infer that HPSO performs better than normal PSO.

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Revised Text:

Bi-clustering has the potential to make significant contributions in the field of information retrieval and web mining, etc. The objective of this paper is to analyze the complex association between users and pages of a web site by using a bi-clustering algorithm. This method can automatically identify the groups of users who show similar expression patterns on a specific subset of the pages.

This paper presents a hybrid binary particle swarm optimization, with a genetic mutation method for the bi-clustering algorithm. This detects the user profile groups according to their coherent browsing behaviors. The interpretation of the bi-clustering results is useful for marketing and sales strategies. The results infer that HPSO performs better than normal PSO.

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