The Handbook of Computational Linguistics and Natural Language ProcessingAlexander Clark, Chris Fox, Shalom Lappin This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP).
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Contents
Statistical Parsing with | |
OtherWork 8 Conclusion | |
Segmentation and Morphology | |
CorpusBased andMachine Learning Methods 6 Concluding Remarks | |
Computational Models of Dialogue 1 Introduction | |
The Challenges of Dialogue | |
Approaches to Dialogue System Design | |
Interaction and Meaning | |
4 | |
5 | |
Computational Semantics | |
Language Model | |
Introduction | |
References | |
Decision Trees | |
Conclusion | |
Evaluation of NLP Systems | |
Artificial Neural Networks | |
Linguistic Annotation | |
Fundamental Concepts | |
Evaluation Paradigms in Common Evaluation Settings | |
Evaluation ofWordSense Disambiguation 5 Case Study Evaluation of Question Answering Systems | |
Summary | |
Domains of Application | |
Speech Recognition 1 Introduction | |
State of the | |
Acoustic Modeling | |
Search | |
The AMI System | |
Research Issues | |
Current Topics | |
Conclusions | |
Statistical Parsing 1 Introduction | |
History | |
Generative Parsing Models | |
Discriminative Parsing Models | |
TransitionBased Approaches | |
Extensions | |
Conclusions | |
Computational Psycholinguistics 1 Introduction | |
ComputationalModels of Human Language Processing | |
Symbolic Models | |
Probabilistic Models | |
Connectionist Models of Sentence Processing | |
HybridModels 7 Concluding Remarks | |
Historical Background 3 Name Extraction 4 Entity Extraction 5 Relation Extraction 6 Event Extraction | |
Concluding Remarks | |
Machine Translation 1 Introduction | |
PhraseBased Statistical | |
Other Approaches to | |
MT Applications | |
Machine Translation at | |
Concluding Remarks and Future Directions | |
Further Reading | |
Making Choices about Language | |
SumTime and SkillSum | |
NLG Choices and Tasks | |
NLG Evaluation | |
Some NLG Research Topics | |
NLG Resources | |
Basic Notions and Terminology | |
Discourse Structure 3 Discourse Coherence | |
Maximum Entropy Models | |
Author Index | |
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Common terms and phrases
algorithm allow analysis annotation answer applications approach assigned Association Chapter classification combined complexity Computational Computational Linguistics conditional Conference consider construct contains context context-free corpus decision tree defined dependency derivation described determining dialogue discourse discussed distribution English error estimation et al evaluation example expressions extraction Figure finite formal function given grammar human important input labeled language model learning lexical Linguistics machine machine translation means methods natural language node noun output pairs parameters parser parsing particular performance phrase position possible predict presented probability problem Proceedings processing produce question recognition referred regular relation representation represented rules semantic sense sentence sequence similar simple space specific speech statistical string structure symbol syntactic tagging task techniques theory training data translation tree University values verb weights word