Article

Revisiting the dependence language model for information retrieval

Authors:

Jean-Pierre ChevalletAuthors Info & Claims

SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 695 - 696

https://doi.org/10.1145/1277741.1277863

Published: 23 July 2007 Publication History

Get Access

Abstract

In this paper, we revisit the dependence language modelfor information retrieval proposed in [1], and show that thismodel is deficient from a theoretical point of view. We thenpropose a new model, well founded theoretically, for integratingdependencies between terms in the language model.This new model is simpler, yet more general, than the oneproposed in [1], and yields similar results in our experiments,on both syntactic and semantic dependencies.

References

[1]

J. Gao, J.-Y. Nie, G. Wu, and G. Cao. Dependence language model for information retrieval. In SIGIR, 2004.

Digital Library

Google Scholar

[2]

C. Lee, G. G. Lee, and M. G. Jang. Dependency structure language model for information retrieval. In ETRI journal, 2006.

Google Scholar

[3]

D. Lin. Dependency-based evaluation of MiniPar. In Workshop on the Evaluation of Parsing Systems, Granada, Spain, May. ACM, 1998.

Google Scholar

[4]

Y. H. H. Lowe and W. Hersh. A pilot study of contextual UMLS indexing to improve the precision of concept-based representation in XML-structured clinical radiology reports. In Conference of the American Medical Informatics Association, 2003.

Google Scholar

[5]

J. M. Ponte and W. B. Croft. A language modeling approach to information retrieval. In SIGIR, 1998.

Digital Library

Google Scholar

[6]

M. Srikanth and R. Srikanth. Biterm language models for document retrieval. In SIGIR, 2002.

Digital Library

Google Scholar

Cited By

View all

Wu HLuk RWong KNie J(2019)Binary Independence Language Model in a Relevance Feedback EnvironmentInternational Journal of Software Engineering and Knowledge Engineering10.1142/S021819401950030X29:06(873-895)Online publication date: 25-Jun-2019
https://doi.org/10.1142/S021819401950030X
Pham TMulhem PMaisonnasse LGaussier ELim J(2012)Visual graph modeling for scene recognition and mobile robot localizationMultimedia Tools and Applications10.1007/s11042-010-0598-860:2(419-441)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1007/s11042-010-0598-8
Goyal PBehera LMcGinnity T(2012)A novel neighborhood based document smoothing model for information retrievalInformation Retrieval10.1007/s10791-012-9202-316:3(391-425)Online publication date: 26-May-2012
https://doi.org/10.1007/s10791-012-9202-3
Show More Cited By

Index Terms

Revisiting the dependence language model for information retrieval
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

Recommendations

Dependence language model for information retrieval
SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

This paper presents a new dependence language modeling approach to information retrieval. The approach extends the basic language modeling approach based on unigram by relaxing the independence assumption. We integrate the linkage of a query as a hidden ...
Cluster-based retrieval using language models
SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

Previous research on cluster-based retrieval has been inconclusive as to whether it does bring improved retrieval effectiveness over document-based retrieval. Recent developments in the language modeling approach to IR have motivated us to re-examine ...
The Study of Methods for Language Model Based Positive and Negative Relevance Feedback in Information Retrieval
ISISE '12: Proceedings of the 2012 Fourth International Symposium on Information Science and Engineering

Relevance feedback techniques are important to Information retrieval (IR), which can effectively improve the performance of IR. The feedback includes positive and negative relevance one. The most of the previous work using feedback have focused on ...

Comments

Information & Contributors

Information

Published In

SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

July 2007

946 pages

ISBN:9781595935977

DOI:10.1145/1277741

General Chairs:
Wessel Kraaij
TNO, The Netherlands
,
Arjen P. de Vries
CWI, The Netherlands
,
Program Chairs:
Charles L. A. Clarke
University of Waterloo, Canada
,
Norbert Fuhr
University of Duisburg-Essen, Germany
,
Noriko Kando
National Institute of Informatics, Japan

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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 July 2007

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

SIGIR07

Sponsor:

SIGIR07: The 30th Annual International SIGIR Conference

July 23 - 27, 2007

Amsterdam, The Netherlands

Acceptance Rates

Overall Acceptance Rate 792 of 3,983 submissions, 20%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

7
Total Citations
View Citations
487
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)1

Reflects downloads up to 02 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Wu HLuk RWong KNie J(2019)Binary Independence Language Model in a Relevance Feedback EnvironmentInternational Journal of Software Engineering and Knowledge Engineering10.1142/S021819401950030X29:06(873-895)Online publication date: 25-Jun-2019
https://doi.org/10.1142/S021819401950030X
Pham TMulhem PMaisonnasse LGaussier ELim J(2012)Visual graph modeling for scene recognition and mobile robot localizationMultimedia Tools and Applications10.1007/s11042-010-0598-860:2(419-441)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1007/s11042-010-0598-8
Goyal PBehera LMcGinnity T(2012)A novel neighborhood based document smoothing model for information retrievalInformation Retrieval10.1007/s10791-012-9202-316:3(391-425)Online publication date: 26-May-2012
https://doi.org/10.1007/s10791-012-9202-3
Park JCroft WSmith D(2011)A quasi-synchronous dependence model for information retrievalProceedings of the 20th ACM international conference on Information and knowledge management10.1145/2063576.2063585(17-26)Online publication date: 24-Oct-2011
https://dl.acm.org/doi/10.1145/2063576.2063585
Pham TMaisonnasse LMulhem PChevallet JQuénot GAl Batal R(2010)MRIM-LIG at ImageCLEF 2009: Robotvision, Image Annotation and Retrieval TasksMultilingual Information Access Evaluation II. Multimedia Experiments10.1007/978-3-642-15751-6_42(324-331)Online publication date: 2010
https://doi.org/10.1007/978-3-642-15751-6_42
Pham TMaisonnasse LMulhem PChevallet JQuénot GAl Batal R(2009)MRIM-LIG at ImageCLEF 2009Proceedings of the 10th international conference on Cross-language evaluation forum: multimedia experiments10.5555/1885110.1885160(324-331)Online publication date: 30-Sep-2009
https://dl.acm.org/doi/10.5555/1885110.1885160
Maisonnasse LGaussier EChevallet J(2008)Multiplying Concept Sources for Graph ModelingAdvances in Multilingual and Multimodal Information Retrieval10.1007/978-3-540-85760-0_73(585-592)Online publication date: 1-May-2008
https://dl.acm.org/doi/10.1007/978-3-540-85760-0_73

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Dependence language model for information retrieval

Cluster-based retrieval using language models

The Study of Methods for Language Model Based Positive and Negative Relevance Feedback in Information Retrieval

Comments

Information

Published In

Sponsors

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations