
Algebraic Structures in Natural Language
$100.28
- Paperback
290 pages
- Release Date
4 October 2024
Summary
Unlocking Language: Algebra vs. Deep Learning in Cognitive Science
Algebraic Structures in Natural Language tackles a core question in cognitive science: how do humans learn and represent language? For years, algebraic systems have been central to formal linguistics, AI, and the psychology of language, viewing linguistic knowledge as rules encoded in grammars and models.
However, the rise of deep learning, with its powerful, non-rule-based mechanism…
Book Details
ISBN-13: | 9781032071046 |
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ISBN-10: | 1032071044 |
Author: | Shalom Lappin, Jean-Philippe Bernardy |
Publisher: | Taylor & Francis Ltd |
Imprint: | CRC Press |
Format: | Paperback |
Number of Pages: | 290 |
Release Date: | 4 October 2024 |
Weight: | 666g |
Dimensions: | 254mm x 178mm |
What They're Saying
Critics Review
“Lappin and Bernardy have assembled a great set of researchers who work on linguistic, cognitive science and natural language processing in deep neural network approaches to language. The result is a state of the art collection of interest to anyone with interests in DNNs and their connection to human language.” –Edward A. F. Gibson, Professor, MIT Department of Brain & Cognitive Sciences
About The Author
Shalom Lappin
Shalom Lappin is a Professor of Computational Linguistics at the University of Gothenburg, Professor of Natural Language Processing at Queen Mary University of London and Emeritus Professor of Computational Linguistics at King’s College London. His research focuses on the application of machine learning and probabilistic models to the representation and the acquisition of linguistic knowledge.
Jean-Philippe Bernardy is a researcher at the University of Gothenburg. His main research interest is in interpretable linguistic models, in particular, those built from first principles of algebra, probability and geometry.
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