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Practical text mining and statistical analysis for non-structured text data applications /

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Miner, Gary
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Academic, 2012.
©2012
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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245 0 0 |a Practical text mining and statistical analysis for non-structured text data applications /  |c Gary Miner [and others]. 
260 |a London :  |b Academic,  |c 2012. 
264 4 |c ©2012 
300 |a 1 online resource (1 volume) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
520 |a 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 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.-Extensive case studies, most in a tutorial format, allow the reader to 'click through' the example using a software program, thus learning to conduct text mining analyses in the most rapid manner of learning possible -Numerous examples, tutorials, power points and datasets available via companion website on Elsevierdirect.com -Glossary of text mining terms provided in the appendix. 
505 0 |a Basic text mining principles -- Introduction to the tutorial and case study section of this book -- Advance topics. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Data mining. 
650 6 |a Exploration de données (Informatique) 
650 7 |a COMPUTERS  |x Database Management  |x Data Mining.  |2 bisacsh 
650 7 |a Data mining  |2 fast 
700 1 |a Miner, Gary. 
776 0 |c Hardback  |z 9780123869791 
856 4 0 |u https://learning.oreilly.com/library/view/~/9780123869791/?ar  |z Texto completo (Requiere registro previo con correo institucional) 
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