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The Naïve Bayes Model for Unsupervised Word Sense Disambiguation (Record no. 23960)

000 -LEADER
fixed length control field 03307nam a22004335i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310151459.0
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 121116s2013 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642336935
978-3-642-33693-5
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA276-280
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5
Edition number 23
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2013.
912 ## -
-- ZDB-2-SMA
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name T. Hristea, Florentina.
Relator term author.
245 14 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title The Naïve Bayes Model for Unsupervised Word Sense Disambiguation
Medium [electronic resource] :
Remainder of title Aspects Concerning Feature Selection /
Statement of responsibility, etc by Florentina T. Hristea.
300 ## - PHYSICAL DESCRIPTION
Extent XIII, 70 p. 4 illus.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title SpringerBriefs in Statistics,
International Standard Serial Number 2191-544X
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1.Preliminaries -- 2.The Naïve Bayes Model in the Context of Word Sense Disambiguation -- 3.Semantic WordNet-based Feature Selection -- 4.Syntactic Dependency-based Feature Selection -- 5.N-Gram Features for Unsupervised WSD with an Underlying Naïve Bayes Model References -- Index.  .
520 ## - SUMMARY, ETC.
Summary, etc This book presents recent advances (from 2008 to 2012) concerning use of the Naïve Bayes model in unsupervised word sense disambiguation (WSD). While WSD, in general, has a number of important applications in various fields of artificial intelligence (information retrieval, text processing, machine translation, message understanding, man-machine communication etc.), unsupervised WSD is considered important because it is language-independent and does not require previously annotated corpora. The Naïve Bayes model has been widely used in supervised WSD, but its use in unsupervised WSD has led to more modest disambiguation results and has been less frequent. It seems that the potential of this statistical model with respect to unsupervised WSD continues to remain insufficiently explored. The present book contends that the Naïve Bayes model needs to be fed knowledge in order to perform well as a clustering technique for unsupervised WSD and examines three entirely different sources of such knowledge for feature selection: WordNet, dependency relations and web N-grams. WSD with an underlying Naïve Bayes model is ultimately positioned on the border between unsupervised and knowledge-based techniques. The benefits of feeding knowledge (of various natures) to a knowledge-lean algorithm for unsupervised WSD that uses the Naïve Bayes model as clustering technique are clearly highlighted. The discussion shows that the Naïve Bayes model still holds promise for the open problem of unsupervised WSD.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistics.
Topical term or geographic name as entry element Computer science.
Topical term or geographic name as entry element Artificial intelligence.
Topical term or geographic name as entry element Statistics.
Topical term or geographic name as entry element Statistics, general.
Topical term or geographic name as entry element Computer Science, general.
Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).
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 9783642336928
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-642-33693-5
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
2014-04-10AUM Main Library2014-04-10 2014-04-10 E-Book   AUM Main Library519.5