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  • 1
    Book
    Book
    New York, NY [u.a.] :Cambridge Univ. Press,
    UID:
    almafu_BV021767262
    Format: XII, 410 S. : , Ill., graph. Darst.
    Edition: 1. publ.
    ISBN: 978-0-521-83657-9 , 0-521-83657-3
    Note: Hier auch später erschienene, unveränderte Nachdrucke
    Language: English
    Subjects: Computer Science , Comparative Studies. Non-European Languages/Literatures
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    Keywords: Text Mining
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    Cambridge :Cambridge University Press,
    UID:
    almahu_9948233951002882
    Format: 1 online resource (xii, 410 pages) : , digital, PDF file(s).
    ISBN: 9780511546914 (ebook)
    Content: Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Similarly, link detection - a rapidly evolving approach to the analysis of text that shares and builds upon many of the key elements of text mining - also provides new tools for people to better leverage their burgeoning textual data resources. The Text Mining Handbook presents a comprehensive discussion of the state-of-the-art in text mining and link detection. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, the book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015). , Introduction to text mining -- Core text mining operations -- Text mining preprocessing techniques -- Categorization -- Clustering -- Information extraction -- Probabilistic models for information extraction -- Preprocessing applications using probabilistic and hybrid approaches -- Presentation-layer considerations for browsing and query refinement -- Visualization approaches -- Link analysis -- Text mining applications.
    Additional Edition: Print version: ISBN 9780521836579
    Language: English
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  • 3
    Online Resource
    Online Resource
    Cambridge ; : Cambridge University Press,
    UID:
    almafu_9960117173702883
    Format: 1 online resource (xii, 410 pages) : , digital, PDF file(s).
    ISBN: 1-107-16150-9 , 1-139-81406-0 , 1-281-04014-2 , 9786611040147 , 1-139-13071-4 , 0-511-33449-4 , 0-511-33383-8 , 0-511-33315-3 , 0-511-54691-2 , 0-511-33507-5
    Content: Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Similarly, link detection - a rapidly evolving approach to the analysis of text that shares and builds upon many of the key elements of text mining - also provides new tools for people to better leverage their burgeoning textual data resources. The Text Mining Handbook presents a comprehensive discussion of the state-of-the-art in text mining and link detection. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, the book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015). , Introduction to text mining -- Core text mining operations -- Text mining preprocessing techniques -- Categorization -- Clustering -- Information extraction -- Probabilistic models for information extraction -- Preprocessing applications using probabilistic and hybrid approaches -- Presentation-layer considerations for browsing and query refinement -- Visualization approaches -- Link analysis -- Text mining applications. , English
    Additional Edition: ISBN 0-521-83657-3
    Language: English
    Subjects: Computer Science , Comparative Studies. Non-European Languages/Literatures
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  • 4
    UID:
    gbv_588757616
    Format: XII, 410 S. , Ill., graph. Darst.
    Edition: Reprinted
    ISBN: 0521836573 , 9780521836579
    Note: Literaturverz. S. 335 - 387
    Language: English
    Subjects: Computer Science
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    Keywords: Text Mining ; Suchmaschine
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