Web Usage Mining: Algorithms and Results

Web Usage Mining: Algorithms and Results

Yew-Kwong Woon (Nanyang Technological University, Singapore), Wee-Keong Ng (Nanyang Technological University, Singapore) and Ee-Peng Lim (Nanyang Technological University, Singapore)
Copyright: © 2005 |Pages: 20
DOI: 10.4018/978-1-59140-414-9.ch018
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Abstract

The rising popularity of electronic commerce makes data mining an indispensable technology for several applications, especially online business competitiveness. The World Wide Web provides abundant raw data in the form of Web access logs. However, without data mining techniques, it is difficult to make any sense out of such massive data. In this chapter, we focus on the mining of Web access logs, commonly known as Web usage mining. We analyze algorithms for preprocessing and extracting knowledge from such logs. We will also propose our own techniques to mine the logs in a more holistic manner. Experiments conducted on real Web server logs verify the practicality as well as the efficiency of the proposed techniques as compared to an existing technique. Finally, challenges in Web usage mining are discussed.

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