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MARC Record from marc_columbia

Record ID marc_columbia/Columbia-extract-20221130-011.mrc:77495363:2504
Source marc_columbia
Download Link /show-records/marc_columbia/Columbia-extract-20221130-011.mrc:77495363:2504?format=raw

LEADER: 02504cam a22003134a 4500
001 5091685
005 20221109215149.0
008 040804s2005 nyua b 001 0 eng
010 $a 2004056524
020 $a0387954333 (alk. paper)
035 $a(OCoLC)ocm56192245
035 $a(NNC)5091685
035 $a5091685
040 $aDLC$cDLC$dOHX$dOrLoB-B
042 $apcc
050 00 $aQA76.9.D343$bT45 2005
072 7 $aQA$2lcco
082 00 $a006.3/12$222
245 00 $aText mining :$bpredictive methods for analyzing unstructured information /$cSholom M. Weiss [and others].
260 $aNew York :$bSpringer,$c2005.
300 $axii, 237 pages :$billustrations ;$c24 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
504 $aIncludes bibliographical references (p. [217]-228) and index.
505 00 $g1.$tOverview of text mining -- $g2.$tFrom textual information to numerical vectors -- $g3.$tUsing text for prediction -- $g4.$tInformation retrieval and text mining -- $g5.$tFinding structure in a document collection -- $g6.$tLooking for information in documents -- $g7.$tCase studies -- $g8.$tEmerging directions -- $gApp.$tSoftware notes.
520 1 $a"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." "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, professionals, 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."--BOOK JACKET.
650 0 $aData mining.$0http://id.loc.gov/authorities/subjects/sh97002073
700 1 $aWeiss, Sholom M.$0http://id.loc.gov/authorities/names/n83161060
852 00 $boff,eng$hQA76.9.D343$iT45 2005