Mining the Web: Discovering Knowledge from Hypertext Data is the first book devoted entirely to techniques for extracting and producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issuesincluding Web crawling and indexingChakrabarti examines machine learning techniques as they relate specifically to the challenges of Web mining and provides applications of machine learning to sytematically acquire, store, and analyze data. Here the focus is on results: the strengths and weaknesses of these applications, along with their potential as foundations for further progress toward a Web that is more aware of content semantics. This thorough and forward-looking book gives the theoretical and practical foundations you need to build innovative applications for mining the Web. Features A comprehensive, critical exploration of statistics-based attempts to make sense of Web data. Details the special challenges associated with analyzing unstructured and semi-structured data. Looks at how classical Information Retrieval techniques have been modified for use with Web data. Focuses on today's dominant learning methods: clustering and classification, hyperlink analysis, and supervised and semi-supervised learning.
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October 01, 2002
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