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Formal multiple-bernoulli models for language modeling

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

Pages 540 - 541

https://doi.org/10.1145/1008992.1009110

Published: 25 July 2004 Publication History

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References

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J. M. Ponte and W. B. Croft. A language modeling approach to information retrieval. In Research and Development in Information Retrieval, pages 275--281, 1998.

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F. Song and W. B. Croft. A general language model for information retrieval. In Proceedings of the eighth international conference on Information and knowledge management, pages 316--321. ACM Press, 1999.

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H. Zaragoza, D. Hiemstra, M. Tipping, and S. Robertson. Bayesian extension to the language model for ad hoc information retrieval. In Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, pages 4--9. ACM Press, 2003.

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C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval. In Research and Development in Information Retrieval, pages 334--342, 2001.

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Najar FBouguila N(2022)On smoothing and scaling language model for sentiment based information retrievalAdvances in Data Analysis and Classification10.1007/s11634-022-00522-617:3(725-744)Online publication date: 13-Oct-2022
https://doi.org/10.1007/s11634-022-00522-6
Balog KRadlinski FArakelyan SPiwowarski BChevalier MGaussier EMaarek YNie JScholer F(2019)Transparent, Scrutable and Explainable User Models for Personalized RecommendationProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331211(265-274)Online publication date: 18-Jul-2019
https://dl.acm.org/doi/10.1145/3331184.3331211
Ying ZHuang JZhou J(2019)A New Digital Signal Processing Based Model With Multi-Aspect Term Frequency for Information RetrievalIEEE Access10.1109/ACCESS.2019.29462887(160738-160754)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2946288
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Index Terms

Formal multiple-bernoulli models for language modeling
1. Information systems
  1. Information retrieval

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Published In

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

July 2004

624 pages

ISBN:1581138814

DOI:10.1145/1008992

General Chair:
Mark Sanderson
University of Sheffield (UK)
,
Program Chairs:
Kalervo Järvelin
University of Tampere (Finland)
,
James Allan
University of Massachusetts (USA)
,
Peter Bruza
Distributed Systems Technology Centre (Australia)

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: 25 July 2004

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SIGIR04

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SIGIR04: The 27th ACM/SIGIR International Symposium on Information Retrieval 2004

July 25 - 29, 2004

Sheffield, United Kingdom

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

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Najar FBouguila N(2022)On smoothing and scaling language model for sentiment based information retrievalAdvances in Data Analysis and Classification10.1007/s11634-022-00522-617:3(725-744)Online publication date: 13-Oct-2022
https://doi.org/10.1007/s11634-022-00522-6
Balog KRadlinski FArakelyan SPiwowarski BChevalier MGaussier EMaarek YNie JScholer F(2019)Transparent, Scrutable and Explainable User Models for Personalized RecommendationProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331211(265-274)Online publication date: 18-Jul-2019
https://dl.acm.org/doi/10.1145/3331184.3331211
Ying ZHuang JZhou J(2019)A New Digital Signal Processing Based Model With Multi-Aspect Term Frequency for Information RetrievalIEEE Access10.1109/ACCESS.2019.29462887(160738-160754)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2946288
Ghosh KBhattacharya AChakraborty PGupta MDey LRoy S(2017)Stopword RemovalProceedings of the 10th Annual ACM India Compute Conference10.1145/3140107.3140125(99-102)Online publication date: 16-Nov-2017
https://dl.acm.org/doi/10.1145/3140107.3140125
Ahmed BGhabayen A(2017)Arabic Automatic Speech Recognition Enhancement2017 Palestinian International Conference on Information and Communication Technology (PICICT)10.1109/PICICT.2017.12(98-102)Online publication date: May-2017
https://doi.org/10.1109/PICICT.2017.12
Ouédraogo FSéré ARouamba ESafiatou S(2017)Analysis of the 2015 Presidential Campaign of Burkina Faso Expressed on Facebooke-Infrastructure and e-Services for Developing Countries10.1007/978-3-319-66742-3_4(33-41)Online publication date: 10-Oct-2017
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Yang PFang HCarterette BFang HLalmas MNie J(2016)A Reproducibility Study of Information Retrieval ModelsProceedings of the 2016 ACM International Conference on the Theory of Information Retrieval10.1145/2970398.2970415(77-86)Online publication date: 12-Sep-2016
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Zheng GCallan JBaeza-Yates RLalmas MMoffat ARibeiro-Neto B(2015)Learning to Reweight Terms with Distributed RepresentationsProceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/2766462.2767700(575-584)Online publication date: 9-Aug-2015
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Lv YZhai C(2015)Negative query generation: bridging the gap between query likelihood retrieval models and relevanceInformation Retrieval Journal10.1007/s10791-015-9257-z18:4(359-378)Online publication date: 6-Jun-2015
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Efron MJones GSheridan PKelly Dde Rijke MSakai T(2013)Query representation for cross-temporal information retrievalProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484054(383-392)Online publication date: 28-Jul-2013
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