by Igor Boshakov, Alexander Gelbukh
Number of pages: 198
The contents of the book are based on the course on computational linguistics that has been delivered by the authors since 1997 at the Center for Computing Research, National Polytechnic Institute, Mexico City. The book focuses on the basic set of ideas and facts from the fundamental science necessary for the creation of intelligent language processing tools, without going deeply into the details of specific algorithms or toy systems.
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by Roger Levy - University of California, San Diego
A book on the topic of using probabilistic models in scientific work on language ranging from experimental data analysis to corpus work to cognitive modeling. The intended audience is graduate students in linguistics, psychology and computer science.
by Dan Jurafsky, James H. Martin - Stanford University
This text takes an empirical approach to the subject, based on applying statistical and machine-learning algorithms to large corporations. The authors describe a unified vision of speech and language processing. Emphasis is on practical applications.
by Joseph D. Booth - Syncfusion, Inc.
Author will guide readers through designing a simple system that can interpret and provide reasonable responses to written English text. With this foundation, readers will be prepared to tackle the greater challenges of natural language development.
by Shuly Wintner - ESSLLI
This text is a mild introduction to Formal Language Theory for students with little or no background in formal systems. The motivation is Natural Language Processing, and the presentation is geared towards NLP applications, with extensive examples.