Recognizing Textual Entailment (Record no. 86152)

000 -LEADER
fixed length control field 03928nam a22005535i 4500
001 - CONTROL NUMBER
control field 978-3-031-02151-0
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730165207.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2013 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031021510
-- 978-3-031-02151-0
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Dagan, Ido.
245 10 - TITLE STATEMENT
Title Recognizing Textual Entailment
Sub Title Models and Applications /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2013.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XX, 204 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Human Language Technologies,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 List of Figures -- List of Tables -- Preface -- Acknowledgments -- Textual Entailment -- Architectures and Approaches -- Alignment, Classification, and Learning -- Case Studies -- Knowledge Acquisition for Textual Entailment -- Research Directions in RTE -- Bibliography -- Authors' Biographies.
520 ## - SUMMARY, ETC.
Summary, etc In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language Understanding capabilities within a very simple interface: recognizing when the meaning of a text snippet is contained in the meaning of a second piece of text. This simple abstraction of an exceedingly complex problem has broad appeal partly because it can be conceived also as a component in other NLP applications, from Machine Translation to Semantic Search to Information Extraction. It also avoids commitment to any specific meaning representation and reasoning framework, broadening its appeal within the research community. This level of abstraction also facilitates evaluation, a crucial component of any technological advancement program. This book explains the RTE task formulation adopted by the NLP research community, and gives a clear overview of research in this area. It draws out commonalities in this research, detailing the intuitions behind dominant approaches and their theoretical underpinnings. This book has been written with a wide audience in mind, but is intended to inform all readers about the state of the art in this fascinating field, to give a clear understanding of the principles underlying RTE research to date, and to highlight the short- and long-term research goals that will advance this technology.
700 1# - AUTHOR 2
Author 2 Roth, Dan.
700 1# - AUTHOR 2
Author 2 Zanzotto, Fabio.
700 1# - AUTHOR 2
Author 2 Sammons, Mark.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-02151-0
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2013.
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-- text
-- txt
-- rdacontent
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-- computer
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-- rdamedia
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-- online resource
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-- text file
-- PDF
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Natural language processing (Computer science).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational linguistics.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Natural Language Processing (NLP).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Linguistics.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1947-4059
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-- ZDB-2-SXSC

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