Probabilistic Models in the Study of Language

Small book cover: Probabilistic Models in the Study of Language

Probabilistic Models in the Study of Language

Publisher: University of California, San Diego
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:
Download link
(4.5MB, PDF)

Similar books

Book cover: Prolog and Natural-Language AnalysisProlog and Natural-Language Analysis
by - Center for the Study of Language
A concise introduction to logic programming and the logic-programming language Prolog both as vehicles for understanding elementary computational linguistics and as tools for implementing the basic components of natural-language-processing systems.
Book cover: Machine Translation: an Introductory GuideMachine Translation: an Introductory Guide
by - Blackwell Pub
This introductory book looks at all aspects of Machine Translation: covering questions of what it is like to use a modern Machine Translation system, through questions about how it is done, to questions of evaluating systems, and more.
Book cover: Natural Language Processing with PythonNatural Language Processing with Python
by - 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.
Book cover: An Introduction to Stochastic Attribute-Value GrammarsAn Introduction to Stochastic Attribute-Value Grammars
This text provides an introduction to the maximum entropy principle and the construction of maximum entropy models for natural language processing. We investigate the implementation of maximum entropy models for attribute-value grammars.