Probabilistic Models in the Study of Language
by Roger Levy
Publisher: University of California, San Diego 2012
Number of pages: 274
A textbook 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, cognitive science, and computer science who are interested in using probabilistic models to study language.
Home page url
Download or read it online for free here:
by Edward Stabler - UCLA
What kind of computational device could use a system like a human language? This text explores the computational properties of devices that could compute morphological and syntactic analyses, and recognize semantic relations among sentences.
by Daniël de Kok, Harm Brouwer
We will go into many of the techniques that so-called computational linguists use to analyze the structure of human language, and transform it into a form that computers work with. We chose Haskell as the main programming language for this book.
by Igor Boshakov, Alexander Gelbukh
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.
by Steven Bird, Ewan Klein, Edward Loper - O'Reilly Media
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies. With it, you'll learn how to write Python programs that work with large collections of unstructured text.