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A neural network for probabilistic information retrieval

Author:

K. L. KwokAuthors Info & Claims

ACM SIGIR Forum, Volume 23, Issue SI

Pages 21 - 30

https://doi.org/10.1145/75335.75338

Published: 01 May 1989 Publication History

Abstract

This paper demonstrates how a neural network may be constructed, together with learning algorithms and modes of operation, that will provide retrieval effectiveness similar to that of the probabilistic indexing and retrieval model based on single terms as document components.

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Cited By

Altinok GKaragoz PBatmaz I(2020)Learning to rank by using multivariate adaptive regression splines and conic multivariate adaptive regression splinesComputational Intelligence10.1111/coin.1241337:1(371-408)Online publication date: 22-Oct-2020
https://doi.org/10.1111/coin.12413
Gross GNagi R(2016)Precedence tree guided search for the efficient identification of multiple situations of interest - AND/OR graph matchingInformation Fusion10.1016/j.inffus.2015.02.00127:C(240-254)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1016/j.inffus.2015.02.001
Mizzaro SPavan MScagnetto I(2015)Content-Based Similarity of Twitter UsersAdvances in Information Retrieval10.1007/978-3-319-16354-3_56(507-512)Online publication date: 2015
https://doi.org/10.1007/978-3-319-16354-3_56
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Index Terms

A neural network for probabilistic information retrieval
1. Computing methodologies
  1. Machine learning
    1. Learning settings
2. Information systems
  1. Information retrieval

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Published In

cover image ACM SIGIR Forum

ACM SIGIR Forum Volume 23, Issue SI

Special issue: Proceedings of the 12th annual international ACMSIGIR conference on Research and development in information retrieval, N.J. Belkin and C.J. van Rijsbergen (Eds.), June 25-28, 1989, Cambridge, MA.

June 1989

243 pages

ISSN:0163-5840

DOI:10.1145/75335

Editors:
Vijay Raghavan
University of Southwestern Louisiana, Lafayette, LA
,
William B. Frakes
AT&T Bell Laboratories, Holmdel, NJ
,
N. J. Belkin,
C. J. van Rijsbergen

Issue’s Table of Contents

SIGIR '89: Proceedings of the 12th annual international ACM SIGIR conference on Research and development in information retrieval
May 1989
257 pages
ISBN:0897913213
DOI:10.1145/75334
Editors:
N. J. Belkin,
C. J. van Rijsbergen

Copyright © 1989 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 May 1989

Published in SIGIR Volume 23, Issue SI

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Cited By

Altinok GKaragoz PBatmaz I(2020)Learning to rank by using multivariate adaptive regression splines and conic multivariate adaptive regression splinesComputational Intelligence10.1111/coin.1241337:1(371-408)Online publication date: 22-Oct-2020
https://doi.org/10.1111/coin.12413
Gross GNagi R(2016)Precedence tree guided search for the efficient identification of multiple situations of interest - AND/OR graph matchingInformation Fusion10.1016/j.inffus.2015.02.00127:C(240-254)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1016/j.inffus.2015.02.001
Mizzaro SPavan MScagnetto I(2015)Content-Based Similarity of Twitter UsersAdvances in Information Retrieval10.1007/978-3-319-16354-3_56(507-512)Online publication date: 2015
https://doi.org/10.1007/978-3-319-16354-3_56
Volpe IMoreira VHuyck C(2011)Cell assemblies for query expansion in Information RetrievalThe 2011 International Joint Conference on Neural Networks10.1109/IJCNN.2011.6033269(551-558)Online publication date: Jul-2011
https://doi.org/10.1109/IJCNN.2011.6033269
Blanco RLioma C(2011)Graph-based term weighting for information retrievalInformation Retrieval10.1007/s10791-011-9172-x15:1(54-92)Online publication date: 28-Jun-2011
https://doi.org/10.1007/s10791-011-9172-x
Hajlaoui KBoucher X(2009)Neural Network Based Text Mining to Discover Enterprise NetworksIFAC Proceedings Volumes10.3182/20090603-3-RU-2001.009942:4(852-857)Online publication date: 2009
https://doi.org/10.3182/20090603-3-RU-2001.0099
Diaz F(2007)Regularizing query-based retrieval scoresInformation Retrieval10.1007/s10791-007-9034-810:6(531-562)Online publication date: 21-Sep-2007
https://doi.org/10.1007/s10791-007-9034-8
Chen HChau M(2005)Web mining: Machine learning for web applicationsAnnual Review of Information Science and Technology10.1002/aris.144038010738:1(289-329)Online publication date: 22-Sep-2005
https://doi.org/10.1002/aris.1440380107
Lee JDubin DGey FHearst MTong R(1999)Context-sensitive vocabulary mapping with a spreading activation networkProceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval10.1145/312624.312678(198-205)Online publication date: 1-Aug-1999
https://dl.acm.org/doi/10.1145/312624.312678
O'Riordan ASorensen HNicholas C(1995)An intelligent agent for high-precision text filteringProceedings of the fourth international conference on Information and knowledge management10.1145/221270.221569(205-211)Online publication date: 2-Dec-1995
https://dl.acm.org/doi/10.1145/221270.221569
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