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Record Nr. |
UNINA9910790470303321 |
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Titolo |
Practical text mining and statistical analysis for non-structured text data applications [[electronic resource] /] / Gary Miner ... [et al.] ; major guest authors, Jennifer Thompson ... [et al] |
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Pubbl/distr/stampa |
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Amsterdam, : Academic Press, 2012 |
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ISBN |
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1-283-39625-4 |
9786613396259 |
0-12-387011-9 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (1095 p.) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Machine generated contents note: Preface: What is TM and what it can do for you Introduction: How to use this book, and chapter summaries Part I: History, Process and Applications of Text Mining; Part II: Tutorials Part III: Areas of Technical Focus in Text Mining Part V: Text Mining Practice and Prospect: The Right Model for the Right Purpose, Summary, and the Future of TM. |
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Sommario/riassunto |
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"The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. This comprehensive professional reference brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. The Handbook of Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications presents a comprehensive how- to reference that shows the user how to conduct text mining and statistically analyze |
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results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities"-- |
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