计算语言学与语言科技原文丛书·词义消歧：算法与应用（英文影印版）

图书标准信息

• 作者 [西班牙]艾吉瑞（Eneko Agirre）、[贡]恩艾克（Philip Eneko） 编
• 出版社 北京大学出版社
• 出版时间 2014-12
• 版次 1
• ISBN 9787301249536
• 定价 64.00元
• 装帧 平装
• 开本 16开
• 纸张 胶版纸
• 页数 364页
• 字数 457千字
• 正文语种 简体中文，英语
• 丛书 计算语言学与语言科技原文丛书

【内容简介】

　　对于计算机来说，要理解人类语言就必须消除歧义，在计算语言学领域，词义消歧（WordSenseDisambiguation，简称WSD）一直是研究者探索的内容本，《计算语言学与语言科技原文丛书·词义消歧：算法与应用（英文影印版）》是近年来国际学术界关于词义消歧研究成果的一部集成之作。几乎覆盖了词义消歧研究各个题目，具有重要学术价值。

【作者简介】

　　　艾吉瑞，西班牙国立巴斯克大学副教授。

【目录】

导读
Contributors
Foreword
Preface
1Introduction
EnekoAgirreandPhilipEdmonds
1.1WordSenseDisambiguation
1.2ABriefHistoryofWSDResearch
1.3WhatisaWordSense?
1.4ApplicationsofWSD
1.5BasicApproachestoWSD
1.6State-of-the-ArtPerformance
1.7PromisingDirections
1.8OverviewofThisBok
1.9FurtherReading
References

2WordSenses
AdamKilgarriff
2.1Introduction
2.2Lexicographers
2.3Philosophy
2.3.1MeaningisSomethingYouDo
2.3.2TheFregeanTraditionandReification
2.3.3TwoIncompatibleSemantics?
2.3.4ImplicationsforWordSenses
2.4Lexicalization
2.5CorpusEvidence
2.5.1LexiconSize
2.5.2Quotations
2.6Conclusion
2.7FurtherReading
Acknowledgments
References

3MakingSenseAboutSense
NancyIdeandYorickWilks
3.1Introduction
3.2WSDandtheLexicographers
3.3WSDandSenseInventories
3.4NLPApplicationsandWSD
3.5WhatLevelofSenseDistinctionsDoWeNeedforNLP,IfAny?
3.6WhatNowforWSD?
3.7Conclusion
References

4EvaluationofWSDSystems
MarthaPalmer,HweeTouNgandHoaTrangDang
4.1Introduction
4.1.1Terminology
4.1.2Overview
4.2Background
4.2.1WordNetandSemcor
4.2.2TheLineandInterestCorpora
4.2.3TheDSOCorpus
4.2.4OpenMindWordExpert
4.3EvaluationUsingPseudo-Words
4.4SensevalEvaluationExercises
4.4.1Senseval-1
EvaluationandScoring
4.4.2Senseval-2
EnglishAll-WordsTask
EnglishLexicalSampleTask
4.4.3ComparisonofTaggingExercises
4.5SourcesofInter-AnnotatorDisagreement
4.6GranularityofSense:GroupingsforWordNet
4.6.1CriteriaforWordNetSenseGrouping
4.6.2AnalysisofSenseGrouping
4.7Senseval-3
4.8Discussion
References

5Knowledge-BasedMethodsforWSD
RadaMihalcea
5.1Introduction
5.2LeskAlgorithm
5.2.1VariationsoftheLeskAlgorithm
SimulatedAnnealing
SimplifiedLeskAlgorithm
AugmentedSemanticSpaces
Summary
5.3SemanticSimilarity
5.3.1MeasuresofSemanticSimilarity
5.3.2UsingSemanticSimilarityWithinaLocalContext
5.3.3UsingSemanticSimilarityWithinaGlobalContext
5.4SelectionalPreferences
5.4.1Preliminaries:LearningWord-to-WordRelations
5.4.2LearningSelectionalPreferences
5.4.3UsingSelectionalPreferences
5.5HeuristicsforWordSenseDisambiguation
5.5.1MostFrequentSense
5.5.2OneSensePerDiscourse
5.5.3OneSensePerCollocation
5.6Knowledge-BasedMethodsatSenseval-2
5.7Conclusions
References

6UnsupervisedCorpus-BasedMethodsforWSD
TedPedersen
6.1Introduction
6.1.1Scope
6.1.2Motivation
DistributionalMethods
TranslationalEquivalence
6.1.3Approaches
6.2Type-BasedDiscrimination
6.2.1RepresentationofContext
6.2.2Algorithms
LatentSemanticAnalysis(LSA)
HyperspaceAnaloguetoLanguage(HAL)
ClusteringByCommittee(CBC)
6.2.3Discussion
6.3Token-BasedDiscrimination
6.3.1RepresentationofContext
6.3.2Algorithms
ContextGroupDiscrimination
McQuitty'sSimilarityAnalysis
6.3.3Discussion
6.4TranslationalEquivalence
6.4.1RepresentationofContext
6.4.2Algorithms
6.4.3Discussion
6.5ConclusionsandtheWayForward
Acknowledgments
References

7SupervisedCorpus-BasedMethodsforWSD
8KnowledgeSourcesforWSD
9AutomaticAcquisitionofLexicalInformationandExamples
10Domain-SpecificWSD
11WSDinNLPApplications