Logo

Computational Linguistics by Igor Boshakov, Alexander Gelbukh

Small book cover: Computational Linguistics

Computational Linguistics
by


ISBN/ASIN: 9703601472
Number of pages: 198

Description:
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.

Home page url

Download or read it online for free here:
Download link
(1.6MB, PDF)

Similar books

Book cover: Notes on Computational LinguisticsNotes on Computational Linguistics
by - 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.
(15023 views)
Book cover: A Maximum Entropy Approach to Natural Language ProcessingA Maximum Entropy Approach to Natural Language Processing
by - Association for Computational Linguistics
The authors describe a method for statistical modeling based on maximum entropy. They present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently.
(9084 views)
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.
(19635 views)
Book cover: Stochastic Attribute-Value GrammarsStochastic Attribute-Value Grammars
by - ESSLLI
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.
(8047 views)