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A Three-layered Web Mining Framework is illustrated in Figure 1, where, the Layer 1 is the Supporting Web Mining Technologies Layer that expounds the various supporting technologies that contribute to Web Mining and the Layer 2 & Layer 3 are Web Mining Concepts Layer & Web Mining Applications Layer respectively. In this paper we attempt to talk about the use of Information Retrieval & Machine Learning Supporting Technologies of Web Mining that drive the next generation of Web search with the key to support relevant search results by effectively and efficiently digging out user- centric information.

Web mining thesis data warehousing and data mining pdf free management phd thesis pdf

Web mining is the term of applying data mining techniques to automatically discover and extract useful information from the World Wide Web documents and services. Although Web mining puts down the roots deeply in data mining, it is not equivalent to data mining. The unstructured feature of Web data triggers more complexity of Web mining. Web mining research is actually a converging area from several research communities, such as Database, Information Retrieval, Artificial Intelligence, and also psychology and statistics as well.


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Web mining involves the analysis of Web server logs of a Web site. The Web server logs contain the entire collection of requests made by a potential or current customer through their browser and responses by the Web server. The information in the logs varies depending on the log file format and option selected on the Web server. Analysis of the Web logs can be insightful for managing the corporate e- business on a short-term basis; the real value of this knowledge is obtained through integration of this resource with other customer touch point information. Common applications include Web site usability, path to purchase, dynamic content marketing, user profiling through behavior analysis and product affinities.