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Efficient Web Log Mining Using Enhanced Apriori Algorithm with Hash Tree and Fuzzy

ISSN:0975-3826
Journal from gdlhub / 2017-08-14 11:52:33
Oleh : S.Veeramalai, N.Jaisankar and A.Kannan, International Journal of Computer Science & Information Technology
Dibuat : 2012-06-26, dengan 1 file

Keyword : Data mining, Web mining, Web log, Association rule, Apriori, Fuzzy.
Subjek : Efficient Web Log Mining Using Enhanced Apriori Algorithm with Hash Tree and Fuzzy
Url : http://airccse.org/journal/jcsit/0810ijcsit06.pdf
Sumber pengambilan dokumen : Internet

Web usage mining is the type of Web mining activity that involves the automatic discovery of user access


patterns from one or more Web servers. In this paper we analyze the pattern using different algorithms like


Apriori, Hash tree and Fuzzy and then we used enhanced Apriori algorithm to give the solution for Crisp


Boundry problem with higher optimized efficiency while comparing to other algorithms.

Deskripsi Alternatif :

Web usage mining is the type of Web mining activity that involves the automatic discovery of user access


patterns from one or more Web servers. In this paper we analyze the pattern using different algorithms like


Apriori, Hash tree and Fuzzy and then we used enhanced Apriori algorithm to give the solution for Crisp


Boundry problem with higher optimized efficiency while comparing to other algorithms.

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