ComputingComputer ScienceInformation TechnologyData MiningRecommender SystemsWeb TechnologiesUser Behavior AnalysisWeb MiningPattern DiscoveryUser Behavior ModelingWeb Usage Mining
The Web’s rapid growth and diversity generate vast amounts of user data, necessitating efficient data mining techniques to organize and retrieve information. This paper surveys existing web usage mining techniques, evaluating their strengths and weaknesses. Web usage mining employs preprocessing, pattern discovery, and analysis of user sessions to uncover usage patterns, with various techniques offering different trade‑offs.
Now a day World Wide Web become very popular and interactive for transferring of information. The web is huge, diverse and active and thus increases the scalability, multimedia data and temporal matters. The growth of the web has outcome in a huge amount of information that is d now freely offered for user access. The several kinds of data have to be handled and organized in a manner that they can be accessed by several users effectively and efficiently. So the usage of data mining methods and knowledge discovery on the web is now on the spotlight of a boosting number of researchers. Web usage mining is a kind of data mining method that can be useful in recommending the web usage patterns with the help of users’ session and behavior. Web usage mining includes three process, namely, preprocessing, pattern discovery and pattern analysis. There are different techniques already exists for web usage mining. Those existing techniques have their own advantages and disadvantages. This paper presents a survey on some of the existing web usage mining techniques.
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