Publications

Mining the Web: Discovering Knowledge from Hypertext Data Soumen Chakrabarti Morgan-Kaufmann Publishers Hard bound, 352 pages ISBN 1558607544

http://www.mkp.com/books_catalog/catalog.asp?ISBN=1-55860-754-4

(Here is a blurb excerpted from the back cover.)

Mining the Web: Discovering Knowledge from Hypertext Data is devoted to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issues, including Web crawling and indexing, I examine machine learning techniques as they relate to the challenges of Web mining. I then describe programs that apply machine learning to systematically acquire, store, and analyze hypertext. Here the focus is on results: the strengths and weaknesses of these applications, along with their potential as foundations for further progress towards a Web that is more aware of content semantics. This book gives the theoretical and practical foundations for building innovative applications for mining the Web, targeted at graduate students, researchers and advanced developers.

Features

• Contains 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 and enhanced for use with Web data.
• Focuses on today's dominant learning methods: clustering and classification, semi-supervised learning, and spectral analysis.
• Presents novel applications for social network analysis and resource discovery.