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Rule Optimization of Web-Logs Data Using Evolutionary Technique

Rule Optimization of Web-Logs Data Using Evolutionary Technique
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Author(s): Manish Kumar (IIIT, Allahabad, India)and Sumit Kumar (IVY Comptech Pvt. Ltd., India)
Copyright: 2015
Pages: 12
Source title: Research Methods: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-7456-1.ch009

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Abstract

Web usage mining can extract useful information from Weblogs to discover user access patterns of Web pages. Web usage mining itself can be classified further depending on the kind of usage data. This may consider Web server data, application server data, or application level data. Web server data corresponds to the user logs that are collected at Web servers. Some of the typical data collected at Web server are the URL requested, the IP address from which the request originated, and timestamp. Weblog data is required to be cleaned, condensed, and transformed in order to retrieve and analyze significant and useful information. This chapter analyzes access frequent patterns by applying the FP-growth algorithm, which is further optimized by using Genetic Algorithm (GA) and fuzzy logic.

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