Online resource; title from PDF title page (EBSCO, viewed June 9, 2017).

Includes bibliographical references and index.

Front Cover; Cognitive Approach to Natural Language Processing; Copyright; Contents; Preface; Bibliography; Chapter 1. Delayed Interpretation, Shallow Processing and Constructions: the Basis of the "Interpret Whenever Possible" Principle ; 1.1. Introduction; 1.2. Delayed processing; 1.3. Working memory; 1.4. How to recognize chunks: the segmentation operations; 1.5. The delaying architecture; 1.6. Conclusion; 1.7. Bibliography; Chapter 2. Can the Human Association Norm Evaluate Machine-Made Association Lists?; 2.1. Introduction; 2.2. Human semantic associations.

2.3. Algorithm efficiency comparison2.4. Conclusion; 2.5. Bibliography; Chapter 3. How a Word of a Text Selects the Related Words in a Human Association Network; 3.1. Introduction; 3.2. The network; 3.3. The network extraction driven by a text-based stimulus; 3.4. Tests of the network extracting procedure; 3.5. A brief discussion of the results and the related work; 3.6. Bibliography; Chapter 4. The Reverse Association Task; 4.1. Introduction; 4.2. Computing forward associations; 4.3. Computing reverse associations; 4.4. Human performance; 4.5. Performance by machine.

4.6. Discussion, conclusions and outlook4.7. Acknowledgments; 4.8. Bibliography; Chapter 5. Hidden Structure and Function in the Lexicon; 5.1. Introduction; 5.2. Methods; 5.3. Psycholinguistic properties of Kernel, Satellites, Core, MinSets and the rest of each dictionary; 5.4. Discussion; 5.5. Future work; 5.6. Bibliography; Chapter 6. Transductive Learning Games for Word Sense Disambiguation ; 6.1. Introduction; 6.2. Graph-based word sense disambiguation; 6.3. Our approach to semi-supervised learning; 6.4. Word sense disambiguation games; 6.5. Evaluation; 6.6. Conclusion; 6.7. Bibliography.

Chapter 7. Use Your Mind and Learn to Write: The Problem of Producing Coherent Text7.1. The problem; 7.2. Suboptimal texts and some of the reasons; 7.3. How to deal with the complexity of the task?; 7.4. Related work; 7.5. Assumptions concerning the building of a tool assisting the writing process; 7.6. Methodology; 7.7. Experiment and evaluation; 7.8. Outlook and conclusion; 7.9. Bibliography; Chapter 8. Stylistic Features Based on Sequential Rule Mining for Authorship Attribut; 8.1. Introduction and motivation; 8.2. The authorship attribution process.

8.3. Stylistic features for authorship attribution8.4. Sequential data mining for stylistic analysis; 8.5. Experimental setup; 8.6. Results and discussion; 8.7. Conclusion; 8.8. Bibliography; Chapter 9. A Parallel, Cognition-oriented Fundamental Frequency Estimation Algorithm ; 9.1. Introduction; 9.2. Segmentation of the speech signal; 9.3. F0 estimation for stable intervals; 9.4. F0 propagation; 9.5. Unstable voiced regions; 9.6. Parallelization; 9.7. Experiments and results; 9.8. Conclusions; 9.9. Acknowledgments; 9.10. Bibliography.

As natural language processing spans many different disciplines, it is sometimes difficult to understand the contributions and the challenges that each of them presents. This book explores the special relationship between natural language processing and cognitive science, and the contribution of computer science to these two fields. It is based on the recent research papers submitted at the international workshops of Natural Language and Cognitive Science (NLPCS) which was launched in 2004 in an effort to bring together natural language researchers, computer scientists, and cognitive and linguistic scientists to collaborate together and advance research in natural language processing. The chapters cover areas related to language understanding, language generation, word association, word sense disambiguation, word predictability, text production and authorship attribution. This book will be relevant to students and researchers interested in the interdisciplinary nature of language processing.

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