Distributional semantics
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 representa...
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| Format: | E-Book |
| Sprache: | English |
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Cambridge
Cambridge University Press
2023
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| Schriftenreihe: | Studies in natural language processing
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| Online-Zugang: | Volltext |
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| 100 | 1 | |a Lenci, Alessandro | |
| 245 | 1 | 0 | |a Distributional semantics |c Alessandro Lenci, Magnus Sahlgren |
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| 520 | |a 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. | ||
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| indexdate | 2024-12-18T12:04:26Z |
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| spelling | Lenci, Alessandro Distributional semantics Alessandro Lenci, Magnus Sahlgren Cambridge Cambridge University Press 2023 1 Online-Ressource (xv, 430 Seiten) txt c cr Studies in natural language processing 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. Sahlgren, Magnus Erscheint auch als Druck-Ausgabe 9781107004290 TUM01 ZDB-20-CTM TUM_PDA_CTM https://doi.org/10.1017/9780511783692 Volltext |
| spellingShingle | Lenci, Alessandro Distributional semantics |
| title | Distributional semantics |
| title_auth | Distributional semantics |
| title_exact_search | Distributional semantics |
| title_full | Distributional semantics Alessandro Lenci, Magnus Sahlgren |
| title_fullStr | Distributional semantics Alessandro Lenci, Magnus Sahlgren |
| title_full_unstemmed | Distributional semantics Alessandro Lenci, Magnus Sahlgren |
| title_short | Distributional semantics |
| title_sort | distributional semantics |
| url | https://doi.org/10.1017/9780511783692 |
| work_keys_str_mv | AT lencialessandro distributionalsemantics AT sahlgrenmagnus distributionalsemantics |