Data-oriented parsing / edited by Rens Bod, Remko Scha, & Khalil Sima'an.

Format:

Book

Contributor:

Bod, Rens, 1965-

Scha, Remko.

Sima'an, Khalil.

Series:

Studies in computational linguistics (Stanford, Calif.)

CSLI Studies in computational linguistics

Language:

English

Subjects (All):

Computational linguistics.

Parsing (Computer grammar).

Linguistics--Statistical methods.

Linguistics.

Physical Description:

xii, 410 pages : illustrations ; 23 cm.

Place of Publication:

Stanford, Calif. : CSLI Publications, [2003]

Summary:

Data-Oriented Parsing (DOP) is one of the leading paradigms in Statistical Natural Language Processing. In this volume, a collection of computational linguists offer a state-of-the-art overview of DOP, suitable for students and researchers in natural language processing and speech recognition as well as for computational linguistics. This handbook begins with the theoretical background of DOP and introduces the algorithms used in DOP as well as in other probabilistic grammar models. After surveying extensions to the basic DOP model, the volume concludes with close study of the applications that use DOP as a backbone: speech understanding, machine translation, and language learning.

Contents:

pt. 1. The basic data-oriented parsing model ; A DOP model for phrase-structure trees / Rens Bod and Remko Scha ; Reconsidering the probability model for DOP / Remko Bonnema and Remko Scha ; Encoding frequency information in stochastic parsing models / John Carroll and David Weir

pt. 2. Computational issues ; Computational complexity of disambiguation under DOP1 / Khalil Sima'an ; Parsing DOP with Monte-Carlo techniques / Jean-Cédric Chappelier and Martin Rajman ; An alternative approach to Monte Carlo parsing / Remko Bonnema ; Efficient parsing of DOP with PCFG-reductions / Joshua Goodman ; An approximation of DOP through memory-based learning / Guy De Pauw ; Compositional partial parsing by memory-based sequence learning / Ido Dagan and Yuval Krymolowski

pt. 3. Richer models ; Tree-gram parsing / Khalil Sima'an ; A DOP model for lexical-functional grammar / Rens Bod and Ronald Kaplan ; A data-driven approach to head-driven phrase structure grammar / Günter Neumann ; Tree adjoining grammars and their application to statistical parsing / Gravind Joshi and Anoop Sarkar ; Localizing dependencies and supertagging / Srinivas Bangalore ; Statistical parsing with an automaticallly extracted tree adjoining grammar / David Chiang ; Extending DOP with insertion / Lars Hoogweg

pt. 4. Beyond parsing ; Machine translation with tree-DOP / Arjen Poutsma ; Machine translation using LFG-DOP / Andy Way ; Alignment-based learning versus data-oriented parsing / Menno van Zaanen

Notes:

Includes bibliographical references and index.

ISBN:

1575864363

1575864355

OCLC:

51454494