Cognitive Approach to Natural Language Processing
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Table of 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.

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Takes a cognitive science perspective and learning from recent advances in cognitive neuroscience, cognitive linguistics and neurolinguistics

About the Author

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 a Professor of Computer Science at Paul Sabatier University, Toulouse, France. Her research focuses on data science, and she has published many books and articles and advised more than 30 PhDs. She leads various international, European and national projects on personal (meta)data privacy and management with applications to deep/machine learning for alert, spam and rumor detection, social emotion and interaction 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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"All in all, for a computer scientist specializing in areas like computational linguistics, natural language processing, robotics, chatbots, navigation systems, speech recognition, and perhaps processing of sign languages, from an interdisciplinary point of view, this is an excellent starting point." --Computer Reviews

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