Knowledge Discovery from Web Usage Data - Research and Development of Sequential Pattern Mining Techniques: A Prospective Study

Shivaprasad,, G and Subbareddy , NV and Acharya, Dinesh U (2010) Knowledge Discovery from Web Usage Data - Research and Development of Sequential Pattern Mining Techniques: A Prospective Study. In: 6th International Conference on Next Generation Web Services Practices, November 23-25, 2010, Gwalior, India.

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Abstract

The rapid expansion of the Web has provided a great opportunity to study user and system behavior by exploring Web access logs. Web Usage mining (WUM) discovers and extracts interesting knowledge/patterns from Web logs. The process of WUM includes three phases: data preprocessing, pattern discovery and pattern analysis [1]. The pattern discovery phase of WUM researches in data mining, machine learning and statistics. Most of this research effort focuses on three main paradigms [2]: association rules [3], sequential patterns, and clustering. Sequential pattern mining, which extracts frequent subsequences from a sequence database, has attracted a great deal of interest during the recent surge in data mining research because it is the basis of many applications, such as Web user analysis, stock trend prediction, and DNA sequence analysis. In this paper, we focus on sequential pattern mining techniques for finding interesting patterns based on Web logs.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: web access logs; web usage mining; sequential pattern mining;
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Depositing User: MIT Library
Date Deposited: 04 Jul 2011 08:49
Last Modified: 04 Jul 2011 08:49
URI: http://eprints.manipal.edu/id/eprint/462

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