Investigation and Analysis of Current Web Mining Techniques as well as Frameworks
Marjan Eshaghi1, S.Z. Gawali2
1Marjan Eshaghi, Department of Information Technology, College of Engineering, Bharati Vidyapeeth University, Pune (M.H), India.
2S.Z. Gawali, Department of Information Technology, College of Engineering, Bharati Vidyapeeth University, Pune (M.H), India.
Manuscript received on 21 March 2013 | Revised Manuscript received on 28 March 2013 | Manuscript published on 30 March 2013 | PP: 178-182 | Volume-2 Issue-1, March 2013 | Retrieval Number: A0518032113/2013©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: Everyone using the Web, experiences how the connection to a popular web site may be very slow during rush hours and it is well known that web users tend to leave a site if the wait time for a page to be served exceeds a given value. Therefore, performance and service quality attributes have gained enormous relevance in service design and deployment. This has led to the development of Web benchmarking tools largely available in the market. One of the most common critics to this approach, is that synthetic workload produced by web stressing tools is far to be realistic. Moreover, Web sites need to be analyzed for discovering commercial rules and user profiles, and models must be extracted from log files and monitored data. This paper deals with a benchmarking methodology based on the integrated usage of web mining techniques and standard web monitoring and assessment tools.
Keywords: Web Mining, Pattern Extraction, Usage Mining, preprocessing.
Scope of the Article: Web Mining