Hardcover. Zustand: Very Good. No Jacket. Missing dust jacket; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
Zustand: Fine. 224 pp., hardcover, previous owner's name neatly inked to the title page, else fine. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.
Hardcover. Zustand: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
EUR 86,75
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In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 89,16
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In den WarenkorbZustand: New. In.
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In den WarenkorbZustand: New. pp. xiv + 207 Illus.
EUR 139,09
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In den WarenkorbZustand: New. Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. Editor(s): Berry, Michael W.; Kogan, Jacob. Num Pages: 222 pages, Illustrations. BIC Classification: UNF. Category: (P) Professional & Vocational. Dimension: 236 x 162 x 18. Weight in Grams: 454. . 2010. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
EUR 97,60
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In den WarenkorbZustand: New. Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. The contributors span several countries and scientific domains: universities, industrial corporations, and gove.
Sprache: Englisch
Verlag: John Wiley & Sons Mär 2010, 2010
ISBN 10: 0470749822 ISBN 13: 9780470749821
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining.