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


Affiliations
1 Department of Information Science and Technology, Anna University, Chennai-600025, Tamil Nadu, India
 

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.

Keywords

Data Mining, Web Mining, Web Log, Association Rule, Apriori, Fuzzy.
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  • Efficient Web Log Mining Using Enhanced Apriori Algorithm with Hash Tree and Fuzzy

Abstract Views: 297  |  PDF Views: 175

Authors

S. Veeramalai
Department of Information Science and Technology, Anna University, Chennai-600025, Tamil Nadu, India
N. Jaisankar
Department of Information Science and Technology, Anna University, Chennai-600025, Tamil Nadu, India
A. Kannan
Department of Information Science and Technology, Anna University, Chennai-600025, Tamil Nadu, India

Abstract


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.

Keywords


Data Mining, Web Mining, Web Log, Association Rule, Apriori, Fuzzy.