Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

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Practical Textual content Mining and Statistical Evaluation for nonstructured Textual content Data Applications includes all the details, tools and strategies a professional will have to efficiently use textual content mining applications and statistical evaluation.

Winner of a 2012 PROSE Award in Processing and Details Sciences from the Association of American Publishers, this reserve presents a thorough how-to reference that presents the user how exactly to conduct textual content mining and statistically evaluate results. Furthermore to offering an in-depth study of core textual content mining and link recognition tools, methods and functions, the reserve examines advanced preprocessing methods, knowledge representation factors, and visualization methods. Finally, the publication explores current real-globe, mission-critical applications of textual content mining and link recognition using real life example tutorials in such varied areas as corporate, financing, business intelligence, genomics analysis, and counterterrorism actions.com

• Considerable case research, most in a tutorial format, permit the reader to ‘click through’ the example utilizing a software program, therefore learning to conduct textual content mining analyses in the most fast manner of learning feasible
• Numerous illustrations, tutorials, power factors and datasets offered via companion website on Elsevierdirect.

  The globe contains an unimaginably huge amount of digital details which gets ever vaster a lot more rapidly.
  

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  See also

  • Design and Analysis: A Researcher's Handbook (4th Edition)
  • Research Methods: A Process of Inquiry (8th Edition)
  • Multilevel Modeling in Plain Language