Automatic Construction of Bayesian Networks for Conversational Agent

As the information in the internet proliferates, the methods for effectively providing the information have been exploited, especially in conversational agents. Bayesian network is applied to infer the intention of user’s query. Since the construction of Bayesian network requires large efforts and m...

Full description

Saved in:
Bibliographic Details
Published inAdvances in Intelligent Computing pp. 228 - 237
Main Authors Lim, Sungsoo, Cho, Sung-Bae
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text
ISBN3540282270
9783540282273
3540282262
9783540282266
ISSN0302-9743
1611-3349
DOI10.1007/11538356_24

Cover

Loading…
Abstract As the information in the internet proliferates, the methods for effectively providing the information have been exploited, especially in conversational agents. Bayesian network is applied to infer the intention of user’s query. Since the construction of Bayesian network requires large efforts and much time, an automatic method for it might be useful for applying conversational agents to several applications. In order to improve the scalability of the agent, in this paper, we propose a method of automatically generating Bayesian networks from scripts composing knowledge base of the conversational agent. It constructs the structure of hierarchically composing nodes and learns the conditional probability distribution table using Noisy-OR gate. The experimental results with subjects confirm the usefulness of the proposed method.
AbstractList As the information in the internet proliferates, the methods for effectively providing the information have been exploited, especially in conversational agents. Bayesian network is applied to infer the intention of user’s query. Since the construction of Bayesian network requires large efforts and much time, an automatic method for it might be useful for applying conversational agents to several applications. In order to improve the scalability of the agent, in this paper, we propose a method of automatically generating Bayesian networks from scripts composing knowledge base of the conversational agent. It constructs the structure of hierarchically composing nodes and learns the conditional probability distribution table using Noisy-OR gate. The experimental results with subjects confirm the usefulness of the proposed method.
Author Lim, Sungsoo
Cho, Sung-Bae
Author_xml – sequence: 1
  givenname: Sungsoo
  surname: Lim
  fullname: Lim, Sungsoo
  email: lss@cs.yonsei.ac.kr
  organization: Dept. of Computer Science, Yonsei University, Seoul, Korea
– sequence: 2
  givenname: Sung-Bae
  surname: Cho
  fullname: Cho, Sung-Bae
  email: sbcho@cs.yonsei.ac.kr
  organization: Dept. of Computer Science, Yonsei University, Seoul, Korea
BackLink http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17095275$$DView record in Pascal Francis
BookMark eNpNkD9PwzAUxA0UibZ04gtkYWAIvGfHcTyW8leqYIE5cly7Ck3tynZB_fYkKgPTO-l-Ot27CRk57wwhVwi3CCDuEDmrGC9rWpyQmRS9LoChBFGdkjGWiDljhTwjk8GgFaUCRmQMDGguRcEuyCTGLwCgQtIxeZjvk9-q1Ops4V1MYa9T613mbXavDia2ymVvJv34sImZ9WGgvk2IaqBUl83XxqVLcm5VF83s707J59Pjx-IlX74_vy7my3xHUaZcQN_GysIw4IKuGq0aU0qGvLS84o0CZFyueFGtgJVWM1TSWOQSqO5f1gWbkutj7k5FrToblNNtrHeh3apwqFGA5FTwnrs5crG33NqEuvF-E2uEetiw_rch-wXgq197
ContentType Book Chapter
Conference Proceeding
Copyright Springer-Verlag Berlin Heidelberg 2005
2005 INIST-CNRS
Copyright_xml – notice: Springer-Verlag Berlin Heidelberg 2005
– notice: 2005 INIST-CNRS
DBID IQODW
DOI 10.1007/11538356_24
DatabaseName Pascal-Francis
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
Applied Sciences
EISBN 9783540319078
3540319077
EISSN 1611-3349
Editor Huang, Guang-Bin
Huang, De-Shuang
Zhang, Xiao-Ping
Editor_xml – sequence: 1
  givenname: De-Shuang
  surname: Huang
  fullname: Huang, De-Shuang
  email: dshuang@iim.ac.cn
– sequence: 2
  givenname: Xiao-Ping
  surname: Zhang
  fullname: Zhang, Xiao-Ping
  email: xiao_ping_zhang@126.com
– sequence: 3
  givenname: Guang-Bin
  surname: Huang
  fullname: Huang, Guang-Bin
  email: egbhuang@ntu.edu.sg
EndPage 237
ExternalDocumentID 17095275
GroupedDBID -DT
-GH
-~X
1SB
29L
2HA
2HV
5QI
875
AASHB
ABMNI
ACGFS
ADCXD
AEFIE
ALMA_UNASSIGNED_HOLDINGS
EJD
F5P
FEDTE
HVGLF
LAS
LDH
P2P
RIG
RNI
RSU
SVGTG
VI1
~02
IQODW
ID FETCH-LOGICAL-p219t-70822f94e30572dbcabe693156f585ba01359d548d036fc31a9ef15902c383c43
ISBN 3540282270
9783540282273
3540282262
9783540282266
ISSN 0302-9743
IngestDate Fri Jan 17 03:47:23 EST 2025
Tue Jul 29 19:44:56 EDT 2025
IsPeerReviewed true
IsScholarly true
Keywords Conditional distribution
Scalability
Database query
User interface
Bayes network
Intention
Logic gate
Knowledge base
Internet
Conditional probability
Artificial intelligence
Intelligent agent
Language English
License CC BY 4.0
LinkModel OpenURL
MeetingName Advances in intelligent computing (Hefei, 23-26 August 2005)
MergedId FETCHMERGED-LOGICAL-p219t-70822f94e30572dbcabe693156f585ba01359d548d036fc31a9ef15902c383c43
PageCount 10
ParticipantIDs pascalfrancis_primary_17095275
springer_books_10_1007_11538356_24
PublicationCentury 2000
PublicationDate 2005
PublicationDateYYYYMMDD 2005-01-01
PublicationDate_xml – year: 2005
  text: 2005
PublicationDecade 2000
PublicationPlace Berlin, Heidelberg
PublicationPlace_xml – name: Berlin, Heidelberg
– name: Berlin
PublicationSeriesTitle Lecture Notes in Computer Science
PublicationSubtitle International Conference on Intelligent Computing, ICIC 2005, Hefei, China, August 23-26, 2005, Proceedings, Part II
PublicationTitle Advances in Intelligent Computing
PublicationYear 2005
Publisher Springer Berlin Heidelberg
Springer
Publisher_xml – name: Springer Berlin Heidelberg
– name: Springer
RelatedPersons Kleinberg, Jon M.
Mattern, Friedemann
Nierstrasz, Oscar
Tygar, Dough
Steffen, Bernhard
Kittler, Josef
Vardi, Moshe Y.
Weikum, Gerhard
Sudan, Madhu
Naor, Moni
Mitchell, John C.
Terzopoulos, Demetri
Pandu Rangan, C.
Kanade, Takeo
Hutchison, David
RelatedPersons_xml – sequence: 1
  givenname: David
  surname: Hutchison
  fullname: Hutchison, David
  organization: Lancaster University, UK
– sequence: 2
  givenname: Takeo
  surname: Kanade
  fullname: Kanade, Takeo
  organization: Carnegie Mellon University, Pittsburgh, USA
– sequence: 3
  givenname: Josef
  surname: Kittler
  fullname: Kittler, Josef
  organization: University of Surrey, Guildford, UK
– sequence: 4
  givenname: Jon M.
  surname: Kleinberg
  fullname: Kleinberg, Jon M.
  organization: Cornell University, Ithaca, USA
– sequence: 5
  givenname: Friedemann
  surname: Mattern
  fullname: Mattern, Friedemann
  organization: ETH Zurich, Switzerland
– sequence: 6
  givenname: John C.
  surname: Mitchell
  fullname: Mitchell, John C.
  organization: Stanford University, CA, USA
– sequence: 7
  givenname: Moni
  surname: Naor
  fullname: Naor, Moni
  organization: Weizmann Institute of Science, Rehovot, Israel
– sequence: 8
  givenname: Oscar
  surname: Nierstrasz
  fullname: Nierstrasz, Oscar
  organization: University of Bern, Switzerland
– sequence: 9
  givenname: C.
  surname: Pandu Rangan
  fullname: Pandu Rangan, C.
  organization: Indian Institute of Technology, Madras, India
– sequence: 10
  givenname: Bernhard
  surname: Steffen
  fullname: Steffen, Bernhard
  organization: University of Dortmund, Germany
– sequence: 11
  givenname: Madhu
  surname: Sudan
  fullname: Sudan, Madhu
  organization: Massachusetts Institute of Technology, MA, USA
– sequence: 12
  givenname: Demetri
  surname: Terzopoulos
  fullname: Terzopoulos, Demetri
  organization: New York University, NY, USA
– sequence: 13
  givenname: Dough
  surname: Tygar
  fullname: Tygar, Dough
  organization: University of California, Berkeley, USA
– sequence: 14
  givenname: Moshe Y.
  surname: Vardi
  fullname: Vardi, Moshe Y.
  organization: Rice University, Houston, USA
– sequence: 15
  givenname: Gerhard
  surname: Weikum
  fullname: Weikum, Gerhard
  organization: Max-Planck Institute of Computer Science, Saarbruecken, Germany
SSID ssj0002792
ssj0000491538
ssj0000315998
Score 1.7554566
Snippet As the information in the internet proliferates, the methods for effectively providing the information have been exploited, especially in conversational...
SourceID pascalfrancis
springer
SourceType Index Database
Publisher
StartPage 228
SubjectTerms Applied sciences
Artificial intelligence
Bayesian network
Computer science; control theory; systems
Conversational agent
Exact sciences and technology
Hierarchical structure
Noisy-OR gate
Script
Title Automatic Construction of Bayesian Networks for Conversational Agent
URI http://link.springer.com/10.1007/11538356_24
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT8MwDI5gXBAH3uKtCHFDRTTpYz1wGC-NCXbhIW5V2ibc1kkrB_j12HXSrYAQcKmmKNoyf41jO_Znxo6yWEgtte9FCkM33dPYU0IYD5vHFUYLXyoM6N8No_5jMHgOn6ftjurqkio7yd-_rSv5D6owBrhilewfkG2-FAbgM-ALT0AYnp-M33aYldKL6fa-zme9aYg1q2Pq0-BOJMy1oYbJ97CtJ2U5vc8v3ah3rlqvTu-1KonJFdt5OoJZNCvP1Zuuqy6HlD1ekzngLEzucGHF3otLpkEh6MnZrb2nGJYVLde1knCapRV6CD-FHlzo8fgHZi4bWcJkVWpZ4oq1QBGDK0NDmnRvhIyKkhhMnT61leN0NAvih_mi9SnRw0flLcMoFcE8m4-7YYct9K4Gt09NzA28IZzTnNRInki3TLQYW_tTL9bygU0Xb4s7se5y5pcwl1ZNYDsZ6oPy5UK9tlMeVtgS1q5wLCoB8a6yOT1aY8tO3NyKe51dNhDzWYh5abiDmDuIOUDM2xDzGuIN9nh99XDR92w_DW8M51Llxcjub5JAg46PRZHlKtNRIsGDN-A0Zgq8gTApwIUtwKwxufRVoo2P_D45_N08kJusMypHeovxCKQicjihwD8Niu6pMjryFdh_shvniYi22UFLLOmYuFNSPwabXsThNjt0ckpxC01Sx589I9yd30zaZYvTd3OPdUBkeh8MxSo7sPh_ANjQYPU
linkProvider Library Specific Holdings
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=bookitem&rft.title=Advances+in+Intelligent+Computing&rft.au=Lim%2C+Sungsoo&rft.au=Cho%2C+Sung-Bae&rft.atitle=Automatic+Construction+of+Bayesian+Networks+for+Conversational+Agent&rft.series=Lecture+Notes+in+Computer+Science&rft.date=2005-01-01&rft.pub=Springer+Berlin+Heidelberg&rft.isbn=9783540282273&rft.issn=0302-9743&rft.eissn=1611-3349&rft.spage=228&rft.epage=237&rft_id=info:doi/10.1007%2F11538356_24
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0302-9743&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0302-9743&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0302-9743&client=summon