Cognitive Approach to Natural Language Processing

Cognitive Approach to Natural Language Processing

Bernadette Sharp, Staffordshire University, UK
Florence Sèdes, Toulouse University, France
Wieslaw Lubaszewski, University of Technology, Poland


ISBN : 9781785482533

Publication Date : May 2017

Hardcover 236 pp

130.00 USD

Co-publisher

Description


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.

Contents


1. Delayed Interpretation, Shallow Processing and Constructions: the Basis of the “Interpret Whenever Possible” Principle.
2. Can the Human Association Norm Evaluate Machine-Made Association Lists?
3. How a Word of a Text Selects the Related Words in a Human Association Network.
4. The Reverse Association Task.
5. Hidden Structure and Function in the Lexicon.
6. Transductive Learning Games for Word Sense Disambiguation.
7. Use Your Mind and Learn to Write: The Problem of Producing Coherent Text.
8. Stylistic Features Based on Sequential Rule Mining for Authorship Attribution.
9. A Parallel, Cognition-oriented Fundamental Frequency Estimation Algorithm.
10. Benchmarking n-grams, Topic Models and Recurrent Neural Networks by Cloze Completions, EEGs and Eye Movements.

About the authors


Bernadette Sharp is Professor of Applied Artificial Intelligence (AI) at Staffordshire University, UK. Her research interests include AI, natural language processing, and text mining. She has been Chair and Editor of the International Workshop for Natural Language Processing and Cognitive Science since 2004.
Florence Sèdes is Professor of Computer Science at Toulouse University, France. Her research areas cover information systems and data management with applications dedicated to multimedia, metadata and mobility in ambient intelligence, social media and CCTV. She supervises a “smart restaurant” platform for emotion and social interaction analysis, and contributes to the ISO 22311 standard.
Wieslaw Lubaszewski is Professor at the Department of Computational Linguistics of the Jagiellonian University and Professor at the Computer Science Department of AGH, University of Technology, in Kraków, Poland. His research interests include natural language dictionaries, text understanding, knowledge representation, and information extraction.

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