Efficient Frequent Pattern Mining in Web Log
Lokesh K. Sharma1, Naresh K. Kar1, Dharmendra K. Roy1 and Ranjana Vyas2
1Department of Information Technology, Rungta College of Engineering and Technology, Kohka-Kurud Road, Bhilai (CG), India.
2School of Information Technology, MATS University, Raipur
Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. The idea is to improve, on the one hand, the results of Web Mining by exploiting the new semantic structures in the Web; and to make use of Web Mining, on the other hand, for building up the Semantic Web. Frequent pattern mining is an important research area in the field of web data mining with wide range of applications. One of them is to use frequent pattern discovery methods in Web log data. The aim of discovering frequent patterns in Web log data is to obtain information about the navigational behaviour of the users. In this paper we give road map of semantic web and web mining and we present P and T tree based pattern mining approaches for the Web usage mining. Our experiment shows that P and T tree based pattern mining approaches is give better performance than existing one.
Keywords: Semantic Web, Web Mining, Web Log data, Frequent pattern discovery.
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