Building Dialogue POMDPs from Expert Dialogues (Record no. 54232)

000 -LEADER
fixed length control field 03429nam a22006015i 4500
001 - CONTROL NUMBER
control field 978-3-319-26200-0
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421111207.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160208s2016 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319262000
-- 978-3-319-26200-0
082 04 - CLASSIFICATION NUMBER
Call Number 621.382
100 1# - AUTHOR NAME
Author Chinaei, Hamidreza.
245 10 - TITLE STATEMENT
Title Building Dialogue POMDPs from Expert Dialogues
Sub Title An end-to-end approach /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2016.
300 ## - PHYSICAL DESCRIPTION
Number of Pages VII, 119 p. 22 illus., 21 illus. in color.
490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Electrical and Computer Engineering,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 1 Introduction -- 2 A few words on topic modeling -- 3 Sequential decision making in spoken dialog management -- 4 Learning the dialog POMDP model components -- 5 Learning the reward function -- 6 Application on healthcare dialog management -- 7 Conclusions and future work.
520 ## - SUMMARY, ETC.
Summary, etc This book discusses the Partially Observable Markov Decision Process (POMDP) framework applied in dialogue systems. It presents POMDP as a formal framework to represent uncertainty explicitly while supporting automated policy solving. The authors propose and implement an end-to-end learning approach for dialogue POMDP model components. Starting from scratch, they present the state, the transition model, the observation model and then finally the reward model from unannotated and noisy dialogues. These altogether form a significant set of contributions that can potentially inspire substantial further work. This concise manuscript is written in a simple language, full of illustrative examples, figures, and tables. Provides insights on building dialogue systems to be applied in real domain Illustrates learning dialogue POMDP model components from unannotated dialogues in a concise format Introduces an end-to-end approach that makes use of unannotated and noisy dialogue for learning each component of dialogue POMDPs.
700 1# - AUTHOR 2
Author 2 Chaib-draa, Brahim.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-26200-0
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2016.
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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
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- User interfaces (Computer systems).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational linguistics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical engineering.
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-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Image and Speech Processing.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- User Interfaces and Human Computer Interaction.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Communications Engineering, Networks.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Linguistics.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2191-8112
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-- ZDB-2-ENG

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