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Mining Web Discovering Knowledge by Chakrabarti Soumen (17 results)
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£ 5.83
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Add to basketCondition: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
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Add to basketPaperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 0.53.
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Mining the Web: Discovering Knowledge from Hypertext Data
Published by MORGAN KAUFMANN PUBL INC, 2002
ISBN 10: 1558607544 ISBN 13: 9781558607545
Language: English
£ 5.95
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Add to basketCondition: Sehr gut. Zustand: Sehr gut | Seiten: 368 | Sprache: Englisch | Produktart: Bücher.
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Mining the Web: Discovering Knowledge from Hypertext Data
Published by Morgan Kaufmann Publishers, 2002
ISBN 10: 1558607544 ISBN 13: 9781558607545
Language: English
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Add to basketHardcover. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 2.05.
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Mining the Web: Discovering Knowledge from Hypertext Data
Published by Morgan Kaufmann Publishers, 2002
ISBN 10: 1558607544 ISBN 13: 9781558607545
Language: English
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Add to basketHardcover. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 2.05.
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Add to basketCondition: Used: Good. Occasion - Bon Etat - Mining the web. Discovering knowledge from hypertext data (2002) - Grand Format.
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Add to basketHardcover. Condition: Very Good. 368 pages. Mining the Web: Discovering Knowledge from Hypertext Data is the first book d evoted entirely to techniques for producing knowledge from the vast body of unst ructured Web data. Building on an initial survey of infrastructural issuesinclud.
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Add to basketHardcover. Condition: Very Good. 1st Edition. In Very Good Condition With No Remarks Or Highlights. 344 Pages With The Index.books are NOT signed. We will state signed at the description section. we confirm they are signed via email or stated in the description box. - Specializing in academic, collectiblle and historically significant, providing the utmost quality and customer service satisfaction. For any questions feel free to email us.
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Mining the Web: Discovering Knowledge from Hypertext Data
Published by Elsevier Science & Technology, 2002
ISBN 10: 1558607544 ISBN 13: 9781558607545
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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£ 56.64
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Add to basketHardback. Condition: New. New copy - Usually dispatched within 4 working days. 658.
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Mining the Web: Discovering Knowledge from Hypertext Data (The Morgan Kaufmann Series in Data Management Systems)
Published by Morgan Kaufmann Publishers In 2002-10-16, 2002
ISBN 10: 1558607544 ISBN 13: 9781558607545
Language: English
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Hardcover. Condition: Brand New. 345 pages. 9.50x7.50x1.00 inches. In Stock.
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£ 84.29
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Mining the Web: Discovering Knowledge from Hypertext Data is the first book devoted entirely to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issues-including Web crawling and indexing-Chakrabarti examines low-level machine learning techniques as they relate specifically to the challenges of Web mining. He then devotes the final part of the book to applications that unite infrastructure and analysis to bring machine learning to bear on systematically acquired and stored data. Here the focus is on results: the strengths and weaknesses of these applications, along with their potential as foundations for further progress. From Chakrabarti's work-painstaking, critical, and forward-looking-readers will gain the theoretical and practical understanding they need to contribute to the Web mining effort. \* A comprehensive, critical exploration of statistics-based attempts to make sense of Web Mining.\* Details the special challenges associated with analyzing unstructured and semi-structured data.\* Looks at how classical Information Retrieval techniques have been modified for use with Web data.\* Focuses on today's dominant learning methods: clustering and classification, hyperlink analysis, and supervised and semi-supervised learning.\* Analyzes current applications for resource discovery and social network analysis.\* An excellent way to introduce students to especially vital applications of data mining and machine learning technology.
