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020 _a9780387345550
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024 7 _a10.1007/978-0-387-34555-0
_2doi
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
072 7 _aUYQE
_2bicssc
072 7 _aCOM021030
_2bisacsh
072 7 _aUNF
_2thema
072 7 _aUYQE
_2thema
082 0 4 _a006.312
_223
100 1 _aWeiss, Sholom M.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_931583
245 1 0 _aText Mining
_h[electronic resource] :
_bPredictive Methods for Analyzing Unstructured Information /
_cby Sholom M. Weiss, Nitin Indurkhya, Tong Zhang, Fred Damerau.
250 _a1st ed. 2005.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2005.
300 _aXII, 237 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aOverview of Text Mining -- From Textual Information to Numerical Vectors -- Using Text for Prediction -- Information Retrieval and Text Mining -- Finding Structure in a Document Collection -- Looking for Information in Documents -- Case Studies -- Emerging Directions.
520 _aOne consequence of the pervasive use of computers is that most documents originate in digital form. Text mining—the process of searching, retrieving, and analyzing unstructured, natural-language text—is concerned with how to exploit the textual data embedded in these documents. Text Mining presents a comprehensive introduction and overview of the field, integrating related topics (such as artificial intelligence and knowledge discovery and data mining) and providing practical advice on how readers can use text-mining methods to analyze their own data. Emphasizing predictive methods, the book unifies all key areas in text mining: preprocessing, text categorization, information search and retrieval, clustering of documents, and information extraction. In addition, it identifies emerging directions for those looking to do research in the area. Some background in data mining is beneficial, but not essential. Topics and features: * Presents a comprehensive and easy-to-read introduction to text mining * Explores the application and utility of the methods, as well as the optimal techniques for specific scenarios * Provides several descriptive case studies that take readers from problem description to system deployment in the real world * Uses methods that rely on basic statistical techniques, thus allowing for relevance to all languages (not just English) * Includes access to downloadable software (runs on any computer), as well as useful chapter-ending historical and bibliographical remarks, a detailed bibliography, and subject and author indexes This authoritative and highly accessible text, written by a team of authorities on text mining, develops the foundation concepts, principles, and methods needed to expand beyond structured, numeric data to automated mining of text samples. Researchers, computer scientists, and advanced undergraduates and graduates with work and interests in data mining, machine learning, databases, and computational linguistics will find the work an essential resource.
650 0 _aData mining.
_93907
650 0 _aComputer networks .
_931572
650 0 _aInformation storage and retrieval systems.
_922213
650 0 _aNatural language processing (Computer science).
_94741
650 0 _aInformation technology—Management.
_931584
650 0 _aDatabase management.
_93157
650 1 4 _aData Mining and Knowledge Discovery.
_931585
650 2 4 _aComputer Communication Networks.
_931586
650 2 4 _aInformation Storage and Retrieval.
_923927
650 2 4 _aNatural Language Processing (NLP).
_931587
650 2 4 _aComputer Application in Administrative Data Processing.
_931588
650 2 4 _aDatabase Management.
_93157
700 1 _aIndurkhya, Nitin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_931589
700 1 _aZhang, Tong.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_931590
700 1 _aDamerau, Fred.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_931591
710 2 _aSpringerLink (Online service)
_931592
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9781441929969
776 0 8 _iPrinted edition:
_z9780387571836
776 0 8 _iPrinted edition:
_z9780387954332
856 4 0 _uhttps://doi.org/10.1007/978-0-387-34555-0
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
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