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Web Usage Mining Techniques for User Browsing Pattern Analysis


Affiliations
1 Singhania University, Rajasthan, India
2 Department of Computer Science and Engineering, T. John Institute of Technology, Bangalore, India
     

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With the rapid growth of the World Wide Web, the use of automated Web-mining techniques to discover useful and relevant information has become increasingly important. One challenging direction is towards Web usage mining, wherein one attempts to discover user navigation patterns of Web usage from Web access logs. Web usage mining is the process of mining web access logs or other user information, user browsing and access patterns on one or more web localities. Web usage mining provides the support for the web site design, providing personalization server and other business making decision, etc. Web mining applies the data mining, the artificial intelligence and so on to the web data and traces users visiting characteristics and then extracts the users using pattern. This article presents an interface for the user to interact dynamically with the dataset and trace the working of the algorithms such as Apriori algorithm and generalized sequential pattern analysis based on timestamp values.

Keywords

Data Mining, World Wide Web, Web Usage Mining, Web Content Mining, Web Structure Mining.
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  • Web Usage Mining Techniques for User Browsing Pattern Analysis

Abstract Views: 202  |  PDF Views: 2

Authors

S. Subashini
Singhania University, Rajasthan, India
T. R. Mahesh
Department of Computer Science and Engineering, T. John Institute of Technology, Bangalore, India

Abstract


With the rapid growth of the World Wide Web, the use of automated Web-mining techniques to discover useful and relevant information has become increasingly important. One challenging direction is towards Web usage mining, wherein one attempts to discover user navigation patterns of Web usage from Web access logs. Web usage mining is the process of mining web access logs or other user information, user browsing and access patterns on one or more web localities. Web usage mining provides the support for the web site design, providing personalization server and other business making decision, etc. Web mining applies the data mining, the artificial intelligence and so on to the web data and traces users visiting characteristics and then extracts the users using pattern. This article presents an interface for the user to interact dynamically with the dataset and trace the working of the algorithms such as Apriori algorithm and generalized sequential pattern analysis based on timestamp values.

Keywords


Data Mining, World Wide Web, Web Usage Mining, Web Content Mining, Web Structure Mining.