Stochastic Attribute-Value Grammars
by Rob Malouf, Miles Osborne
Publisher: ESSLLI 2001
Number of pages: 159
Description:
This one-week course will provide an introduction to the maximum entropy principle and the construction of maximum entropy models for natural language processing. Through a combination of lectures and, as local computing facilities permit, hands-on lab exercises, students will investigate the implementation of maximum entropy models for attribute-value grammars, including such topics as ambiguity identification, feature selection, and model training and evaluation.
Download or read it online for free here:
Download link
(1.8MB, PDF)
Similar books

by Jon Barwise, John Etchemendy - Center for the Study of Language
The book covers the boolean connectives, formal proof techniques, quantifiers, basic set theory, induction, proofs of soundness and completeness for propositional and predicate logic, and an accessible sketch of Godel's first incompleteness theorem.
(18821 views)

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.
(15027 views)

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.
(15489 views)

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.
(5975 views)