Distributional Semantics
Published on 21. September 2023
Book
Hardback
448 pages
978-1-107-00429-0 (ISBN)
Description
Distributional semantics develops theories and methods to represent the meaning of natural language expressions, with vectors encoding their statistical distribution in linguistic contexts. It is at once a theoretical model to express meaning, a practical methodology to construct semantic representations, a computational framework for acquiring meaning from language data, and a cognitive hypothesis about the role of language usage in shaping meaning. This book aims to build a common understanding of the theoretical and methodological foundations of distributional semantics. Beginning with its historical origins, the text exemplifies how the distributional approach is implemented in distributional semantic models. The main types of computational models, including modern deep learning ones, are described and evaluated, demonstrating how various types of semantic issues are addressed by those models. Open problems and challenges are also analyzed. Students and researchers in natural language processing, artificial intelligence, and cognitive science will appreciate this book.
Reviews / Votes
'Lenci and Sahlgren's textbook is a landmark contribution to the fast growing and increasingly important discipline of distributional semantics. They have managed to distill 60 years of diverse research on distributional semantics, from its beginning in structural and corpus linguistics and psychology, through the application of techniques from information retrieval and linear algebra, to the most recent developments driven by deep neural networks and large language models in NLP. The authors synthesize the major findings from different fields and integrate these diverse traditions into a comprehensive and coherent framework of distributional meaning. Lenci and Sahlgren's text promises to be the new standard for reference and teaching in this area.' James Pustejovsky, Brandeis University 'It is a significant contribution to both linguistic theory and computational linguistics in its own right, providing a bridge between semantic theories and practical applications in natural language processing (NLP). As both a linguist and computational linguist, I found this book relevant to current computational as well as formal semantic research, which increasingly employs distributional methods to understand and model language meaning ... Lenci and Sahlgren's book is important, as it presents an impressive treatment of the historical and theoretical foundations of distributional semantics ... By providing a clear and rigorous account of how meaning can be modeled through usage patterns, Lenci and Sahlgren contribute to ongoing debates in semantics and cognitive science dating back 70 years. Their book supports the view that meaning in language can be understood through its distributional properties, which can in turn help linguists better understand the formal properties inherent in language meaning.' James Pustejovsky, WORD 'With this book, Lenci and Sahlgren promote the dissemination of distributional semantics. These studies contribute, on the one hand, to establishing contact with other theories of meaning representation and, on the other, to comparing them with existing ones. This enriches the landscape of semantics and helps us better understand it, as it offers different perspectives for approaching the subject in question. The growing relevance of NLP and AI today finds perfect application in these theories, which serves to confirm the natural progress of semantic theories.' Paloma Sanchez Hernandez, International Journal of Ibero-American LinguisticsMore details
Series
Language
English
Place of publication
Cambridge
United Kingdom
Target group
College/higher education
Product notice
sewn/stitched
Cloth over boards
Illustrations
Worked examples or Exercises
Dimensions
Height: 233 mm
Width: 154 mm
Thickness: 30 mm
Weight
752 gr
ISBN-13
978-1-107-00429-0 (9781107004290)
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Schweitzer Classification
Persons
Alessandro Lenci, PhD, is Professor of Linguistics and Director of the Computational Linguistics Laboratory at the University of Pisa. His research interests include distributional semantics, computational linguistics, and natural language processing. The recipient of the '10-year Test-of-Time-Award' from the Association for Computational Linguistics in 2020, he has published extensively and coordinated many projects on natural language processing and cognitive science. Magnus Sahlgren, PhD, is Head of Research for Natural Language Understanding at AI Sweden. Known primarily for research on computational models of meaning, Sahlgren's work lies at the intersection of computational linguistics, machine learning, and artificial intelligence. His doctoral dissertation, entitled 'The Word-Space Model,' was awarded the prize for the 'Most Prominent Scholarly Achievement of 2006' by the Stockholm University Faculty of Humanities.
Content
Preface; Part I. Theory: 1. From usage to meaning: the foundations of distributional semantics; 2. Distributional representations; Part II. Models: 3. Distributional semantic models; 4. Matrix models; 5. Random encoding models; Part III. Practice: 7. Evaluation of distributional semantic models; 8. Distributional semantics and the lexicon; 9 Distributional semantics beyond the lexicon; 10. Conclusions and Outlook; References; Index.