國立虎尾科技大學 |

Language: English

Back

Embeddings in natural language processing : = theory and advances in vector representations of meaning /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Embeddings in natural language processing :/ Mohammad Taher Pilehvar, Jose Camacho-Collados.
Reminder of title:	theory and advances in vector representations of meaning /
Author:	Pilehvar, Mohammad Taher.
other author:	Camacho-Collados, Jose.
Published:	[San Rafael, Calif.] :Morgan & Claypool, : c2021.,
Description:	xvii, 157 p. :ill. ; : 24 cm.;
Subject:	Programming languages (Electronic computers) - Semantics. -
ISBN:	9781636390215 (pbk.) :

Embeddings in natural language processing : = theory and advances in vector representations of meaning /
Pilehvar, Mohammad Taher.

Embeddings in natural language processing :theory and advances in vector representations of meaning /Mohammad Taher Pilehvar, Jose Camacho-Collados. - [San Rafael, Calif.] :Morgan & Claypool,c2021. - xvii, 157 p. :ill. ;24 cm. - Synthesis lectures on human language technologies,#471947-4040 ;. - Synthesis lectures on human language technologies ;#18. .

Includes bibliographical references (p. 111-155).

Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.

ISBN: 9781636390215 (pbk.) :NT1947Subjects--Topical Terms:

674560
Programming languages (Electronic computers)
--Semantics.

LC Class. No.: QA76.9.N38 / P554 2021

Dewey Class. No.: 006.3/5

Embeddings in natural language processing : = theory and advances in vector representations of meaning /
LDR:02036cam a2200217 a 4500 001 1065664
003 NhCcYBP
005 20210316170745.6
008 220831s2021 caua b 000 0 eng d
020 $a 9781636390215 (pbk.) : $c NT1947
020 $a 9781636390239 (cloth)
020 $z 9781636390222 (ebook)
035 $a om827597362
040 $a YDX $b eng $c YDX $d YDX $d STF $d OCLCO $d OCLCF $d YDXIT $d NFU
050 4 $a QA76.9.N38 $b P554 2021
082 0 4 $a 006.3/5 $2 23
100 1 $a Pilehvar, Mohammad Taher. $3 1370993
245 1 0 $a Embeddings in natural language processing : $b theory and advances in vector representations of meaning / $c Mohammad Taher Pilehvar, Jose Camacho-Collados.
260 $a [San Rafael, Calif.] : $b Morgan & Claypool, $c c2021.
300 $a xvii, 157 p. : $b ill. ; $c 24 cm.
490 1 $a Synthesis lectures on human language technologies, $x 1947-4040 ; $v #47
504 $a Includes bibliographical references (p. 111-155).
520 $a Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.
650 0 $a Programming languages (Electronic computers) $x Semantics. $3 674560
650 0 $a Artificial intelligence. $3 559380
650 0 $a Natural language processing (Computer science) $3 641811
700 1 $a Camacho-Collados, Jose. $3 1370994
830 0 $a Synthesis lectures on human language technologies ; $v #18. $3 931364