Abstract
Abstract This paper presents a comprehensive survey of web log/usage mining based on over 100 research papers. This is the first survey
dedicated exclusively to web log/usage mining. The paper identifies several web log mining sub-topics including specific onessuch as data cleaning, user and session identification. Each sub-topic is explained, weaknesses and strong points are discussedand possible solutions are presented. The paper describes examples of web log mining and lists some major web log mining softwarepackages.
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