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Coarse-to-Fine Natural Language Processing (Record no. 15654)

000 -LEADER
fixed length control field 03144nam a22003855i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310145534.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 111102s2012 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642227431
978-3-642-22743-1
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA75.5-76.95
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 004
Edition number 23
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2012.
912 ## -
-- ZDB-2-SHU
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Petrov, Slav.
Relator term author.
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Coarse-to-Fine Natural Language Processing
Medium [electronic resource] /
Statement of responsibility, etc by Slav Petrov.
300 ## - PHYSICAL DESCRIPTION
Extent XXII, 106 p.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Theory and Applications of Natural Language Processing,
International Standard Serial Number 2192-032X
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1.Introduction -- 2.Latent Variable Grammars for Natural Language Parsing -- 3.Discriminative Latent Variable Grammars -- 4.Structured Acoustic Models for Speech Recognition -- 5.Coarse-to-Fine Machine Translation Decoding -- 6.Conclusions and Future Work -- Bibliography.
520 ## - SUMMARY, ETC.
Summary, etc The impact of computer systems that can understand natural language will be tremendous. To develop this capability we need to be able to automatically and efficiently analyze large amounts of text. Manually devised rules are not sufficient to provide coverage to handle the complex structure of natural language, necessitating systems that can automatically learn from examples. To handle the flexibility of natural language, it has become standard practice to use statistical models, which assign probabilities for example to the different meanings of a word or the plausibility of grammatical constructions. This book develops a general coarse-to-fine framework for learning and inference in large statistical models for natural language processing. Coarse-to-fine approaches exploit a sequence of models which introduce complexity gradually. At the top of the sequence is a trivial model in which learning and inference are both cheap. Each subsequent model refines the previous one, until a final, full-complexity model is reached. Applications of this framework to syntactic parsing, speech recognition and machine translation are presented, demonstrating the effectiveness of the approach in terms of accuracy and speed. This book is intended for students and researchers interested in statistical approaches to Natural Language Processing.  Slav’s work Coarse-to-Fine Natural Language Processing represents a major advance in the area of syntactic parsing, and a great advertisement for the superiority of the machine-learning approach. Eugene Charniak (Brown University)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
Topical term or geographic name as entry element Computer Science.
Topical term or geographic name as entry element Computer Science, general.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783642227424
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-642-22743-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type E-Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Damaged status Lost status Withdrawn status Current location Full call number
2014-04-02AUM Main Library2014-04-02 2014-04-02 E-Book   AUM Main Library004