| 书目名称 | Neural Representations of Natural Language |
| 编辑 | Lyndon White,Roberto Togneri,Mohammed Bennamoun |
| 视频video | |
| 概述 | Enriches readers’ understanding of how neural networks create a machine interpretable representation of the meaning of natural language.Absolutely packed with useful insights drawn from experience usi |
| 丛书名称 | Studies in Computational Intelligence |
| 图书封面 |  |
| 描述 | .This book offers an introduction to modern natural language processing using machine learning, focusing on how neural networks create a machine interpretable representation of the meaning of natural language. Language is crucially linked to ideas – as Webster’s 1923 “English Composition and Literature” puts it: “A sentence is a group of words expressing a complete thought”. Thus the representation of sentences and the words that make them up is vital in advancing artificial intelligence and other “smart” systems currently being developed. Providing an overview of the research in the area, from Bengio et al.’s seminal work on a “Neural Probabilistic Language Model” in 2003, to the latest techniques, this book enables readers to gain an understanding of how the techniques are related and what is best for their purposes. As well as a introduction to neural networks in general and recurrent neural networks in particular, this book details the methods used for representing words, senses of words, and larger structures such as sentences or documents. The book highlights practical implementations and discusses many aspects that are often overlooked or misunderstood. The book includes tho |
| 出版日期 | Book 2019 |
| 关键词 | Natural Language Processing; Machine Learning; Vector Representations; Word Embeddings; Learned Represen |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-13-0062-2 |
| isbn_softcover | 978-981-13-4320-9 |
| isbn_ebook | 978-981-13-0062-2Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | Springer Nature Singapore Pte Ltd. 2019 |
发表于 2025-3-21 16:38:53
