A Comparative Study between Web Mining Tools over some WUM Algorithms to Analyze Web Access Logs
Arvind K. Sharma

 Arvind K. Sharma, Ph.D Computer Science Research Scholar, School of  Engineering & Technology, Jaipur, India.
Manuscript received on May 01, 2012. | Revised Manuscript received on May 28, 2012. | Manuscript Published on June 10, 2012. | PP: 58-66 | Volume-1 Issue-1, June 2012. | Retrieval Number: A118051112/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper has attempted to provide an up-to-date survey of the rapidly growing area of Web usage mining, which is the demand of current technology. In this paper, we present an overview of the various research areas in Web data mining and then focus on the Web usage mining tools and techniques. Web mining continues to remain as a potential research area in the present scenario. In this context, the various Web usage mining algorithms are discussed and their relative comparison of merits and demerits are also presented and the most appropriate ones are selected based on the characteristics of the data available from the Web server log files. Finally, we have investigated three powerful Web usage mining tools. The use of these tools is also illustrated through the analysis of one case study. The results of Web usage mining need to be visualised in order to assist with their analysis and interpretation. 
Keywords: Web Data Mining, Web logs, WUM Tools.