Article

A platform for Okapi-based contextual information retrieval

Authors:

Xiangji Huang,

Miao Wen,

Aijun An,

Yan-Rui HuangAuthors Info & Claims

SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval

Page 728

https://doi.org/10.1145/1148170.1148341

Published: 06 August 2006 Publication History

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Abstract

We present an extensible java-based platform for contextual retrieval based on the probabilistic information retrieval model. Modules for dual indexes, relevance feedback with blind or machine learning approaches and query expansion with context are integrated into the Okapi system to deal with the contextual information. This platform allows easy extension to include other types of contextual information.

Reference

[1]

Xiangji Huang, Yan-Rui Huang, Miao Wen. A Dual Index Model for Contextual Information Retrieval. In Proc. of the 28th ACM SIGIR 2005.

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Wani STengku Sembok TMir M(2018)Context Aware Knowledge Bases for Efficient Contextual Retrieval: Design and MethodologiesComputational Science and Technology10.1007/978-981-13-2622-6_55(569-579)Online publication date: 28-Aug-2018
https://doi.org/10.1007/978-981-13-2622-6_55
Cercone, F'IEEE N(2015)What's the big deal about big data?Big Data and Information Analytics10.3934/bdia.2016.1.311:1(31-79)Online publication date: Sep-2015
https://doi.org/10.3934/bdia.2016.1.31
Zhao JHuang JYe Z(2014)Modeling Term Associations for Probabilistic Information RetrievalACM Transactions on Information Systems (TOIS)10.1145/259098832:2(1-47)Online publication date: 1-Apr-2014
https://dl.acm.org/doi/10.1145/2590988
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Index Terms

A platform for Okapi-based contextual information retrieval
1. Information systems
  1. Information retrieval

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Published In

SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval

August 2006

768 pages

ISBN:1595933697

DOI:10.1145/1148170

General Chair:
Efthimis N. Efthimiadis
University of Washington
,
Program Chairs:
Susan Dumais
Microsoft Research, Redmond
,
David Hawking
CSIRO ICT Centre, Canberra, Australia
,
Kalervo Järvelin,
University of Tampere, Finland

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: 06 August 2006

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SIGIR06

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SIGIR06: The 29th Annual International SIGIR Conference

August 6 - 11, 2006

Washington, Seattle, USA

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

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Wani STengku Sembok TMir M(2018)Context Aware Knowledge Bases for Efficient Contextual Retrieval: Design and MethodologiesComputational Science and Technology10.1007/978-981-13-2622-6_55(569-579)Online publication date: 28-Aug-2018
https://doi.org/10.1007/978-981-13-2622-6_55
Cercone, F'IEEE N(2015)What's the big deal about big data?Big Data and Information Analytics10.3934/bdia.2016.1.311:1(31-79)Online publication date: Sep-2015
https://doi.org/10.3934/bdia.2016.1.31
Zhao JHuang JYe Z(2014)Modeling Term Associations for Probabilistic Information RetrievalACM Transactions on Information Systems (TOIS)10.1145/259098832:2(1-47)Online publication date: 1-Apr-2014
https://dl.acm.org/doi/10.1145/2590988
An XHuang JJones GSheridan PKelly Dde Rijke MSakai T(2013)Boosting novelty for biomedical information retrieval through probabilistic latent semantic analysisProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484174(829-832)Online publication date: 28-Jul-2013
https://dl.acm.org/doi/10.1145/2484028.2484174
Babashzadeh AHuang JDaoud MJones GSheridan PKelly Dde Rijke MSakai T(2013)Exploiting semantics for improving clinical information retrievalProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484167(801-804)Online publication date: 28-Jul-2013
https://dl.acm.org/doi/10.1145/2484028.2484167
Daoud MHuang J(2013)Mining query-driven contexts for geographic and temporal searchInternational Journal of Geographical Information Science10.1080/13658816.2012.75688327:8(1530-1549)Online publication date: 26-Mar-2013
https://doi.org/10.1080/13658816.2012.756883
Babashzadeh ADaoud MHuang J(2013)Using semantic-based association rule mining for improving clinical text retrievalProceedings of the second international conference on Health Information Science10.1007/978-3-642-37899-7_16(186-197)Online publication date: 25-Mar-2013
https://dl.acm.org/doi/10.1007/978-3-642-37899-7_16
Ye ZHuang JLin H(2011)Incorporating rich features to boost information retrieval performanceExpert Systems with Applications: An International Journal10.1016/j.eswa.2010.12.10838:6(7569-7574)Online publication date: 1-Jun-2011
https://dl.acm.org/doi/10.1016/j.eswa.2010.12.108
Hu QHuang XZhang ABorodovsky MOzsoyoglu GMikler A(2010)Genomics information retrieval using a Bayesian model for learning and re-rankingProceedings of the First ACM International Conference on Bioinformatics and Computational Biology10.1145/1854776.1854846(426-429)Online publication date: 2-Aug-2010
https://dl.acm.org/doi/10.1145/1854776.1854846
Huang XHu QAllan JAslam JSanderson MZhai CZobel J(2009)A bayesian learning approach to promoting diversity in ranking for biomedical information retrievalProceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval10.1145/1571941.1571995(307-314)Online publication date: 19-Jul-2009
https://dl.acm.org/doi/10.1145/1571941.1571995
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