Synopsis
This book provides a comprehensive foundation for the use of distributional methods in computational modeling of meaning.
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About the Authors
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.
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Distributional Semantics
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ISBN 10: 1107004292
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Distributional Semantics (Hardcover)
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Hardcover. Condition: new. Hardcover. 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. This book provides a comprehensive foundation of distributional methods in computational modeling of meaning. It aims to build a common understanding of the theoretical and methodological foundations for students of computational linguistics, natural language processing, computer science, artificial intelligence, and cognitive science. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781107004290
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Distributional Semantics (Studies in Natural Language Processing)
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Hardcover. Condition: new. Hardcover. 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. This book provides a comprehensive foundation of distributional methods in computational modeling of meaning. It aims to build a common understanding of the theoretical and methodological foundations for students of computational linguistics, natural language processing, computer science, artificial intelligence, and cognitive science. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781107004290
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