text mining classification clustering (17 Ergebnisse)

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 automatic-just 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 today's 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 26-28, 2007). With close to 60 applied mathematicians and computer scientists representing universities, industrial corporations, and government laboratories, the workshop f- tured both invited and contributed talks on important topics such as the application of techniques of machine learning in conjunction with natural language processing, - formation extraction and algebraic/mathematical approaches to computational inf- mation retrieval. The workshop's program also included an Anomaly Detection/Text Mining competition. NASA Ames Research Center of Moffett Field, CA, and SAS Institute Inc. of Cary, NC, sponsored the workshop.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 automatic-just 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 today's 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 26-28, 2007). With close to 60 applied mathematicians and computer scientists representing universities, industrial corporations, and government laboratories, the workshop f- tured both invited and contributed talks on important topics such as the application of techniques of machine learning in conjunction with natural language processing, - formation extraction and algebraic/mathematical approaches to computational inf- mation retrieval. The workshop's program also included an Anomaly Detection/Text Mining competition. NASA Ames Research Center of Moffett Field, CA, and SAS Institute Inc. of Cary, NC, sponsored the workshop.

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Taschenbuch. Zustand: Neu. Survey of Text Mining | Clustering, Classification, and Retrieval | Michael W. Berry | Taschenbuch | xvii | Englisch | 2011 | Springer | EAN 9781441930576 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory.As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments.This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.

Paperback. Zustand: Brand New. 2004 edition. 261 pages. 9.21x6.06x0.94 inches. In Stock.