Survey of Text Mining II Clustering, Classification, and Retrieval [Hardcover]

This Second Edition brings readers thoroughly up to date with the emerging field of text mining, the application of techniques of machine learning in conjunction with natural language processing, information extraction, and algebraic/mathematical approaches to computational information retrieval. The book explores a broad range of issues, ranging from the development of new learning approaches to the parallelization of existing algorithms. Authors highlight open research questions in document categorization, clustering, and trend detection. In addition, the book describes new application problems in areas such as email surveillance and anomaly detection.

This Second Edition explores the field of text mining. Coverage includes the use of machine learning in conjunction with natural language processing, information extraction, and algebraic/mathematical approaches to computational information retrieval.

As we enter the third decade of the World Wide Web (WWW), the textual revolution has seen a tremendous change in the availability of online information. Finding inf- mation for just about any need has never been more automaticjust a keystroke or mouseclick away. While the digitalization and creation of textual materials continues at light speed, the ability to navigate, mine, or casually browse through documents too numerous to read (or print) lags far behind. What approaches to text mining are available to ef?ciently organize, classify, label, and extract relevant information for todays information-centric users? What algorithms and software should be used to detect emerging trends from both text streamsandarchives?Thesearejustafewoftheimportantquestionsaddressedatthe Text Mining Workshop held on April 28, 2007, in Minneapolis, MN. This workshop, the ?fth in a series of annual workshops on text mining, was held on the ?nal day of the Seventh SIAM International Conference on Data Mining (April 2628, 2007). With close to 60 appliedlC!