Text And Text Processing
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Speech and Language Processing
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.
Text Processing in Python
bull; Demonstrates how Python is the perfect language for text-processing functions. bull; Provides practical pointers and tips that emphasize efficient, flexible, and maintainable approaches to text-processing challenges. bull; Helps programmers develop solutions for dealing with the increasing amounts of data with which we are all inundated.
Text Processing with Ruby
"Whatever you want to do with text, Ruby is up to the job. Most information in the world is in text format, and you need to make sense of the data hiding within. You want to do this efficiently, avoiding labor-intensive, manual work. Text Processing with Ruby takes a practical approach to working with text. First, Aquire: Explore Ruby's core and standard library, and extract text into your Ruby programs. Process delimited files and web pages, and write utilities. Second, Transform: Use regular expressions, write a parser, and use Natural Language Processing techniques. Finally, Load: Write the transformed text and data to standard output, files, and other processes. Serialize text into JSON, XML, and CVS, and use ERB to create more complex formats. You'll soon be able to tackle even the most enormous and entangled text with ease."--Back cover.