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.
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Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. pp. xiv + 207 Illus.
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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.
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In den WarenkorbGebunden. Zustand: 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. This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine learning, and natural language processing can collectively capture, classify, and interpret words and their contexts. As suggested in the preface, text mining is needed when 'words are not enough.' This book: - Provides state-of-the-art algorithms and techniques for critical tasks in text mining applications, such as clustering, classification, anomaly and trend detection, and stream analysis. - Presents a survey of text visualization techniques and looks at the multilingual text classification problem. - Discusses the issue of cybercrime associated with chatrooms. - Features advances in visual analytics and machine learning along with illustrative examples. - Is accompanied by a supporting website featuring datasets. Applied mathematicians, statisticians, practitioners and students in computer science, bioinformatics and engineering will find this book extremely useful.