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An Information Retrieval Experiment Framework for Domain Specific Applications

Authors:

Harrisen Scells,

Daniel Locke,

Guido ZucconAuthors Info & Claims

SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval

Pages 1281 - 1284

https://doi.org/10.1145/3209978.3210167

Published: 27 June 2018 Publication History

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Abstract

We present a framework for constructing and executing information retrieval experiment pipelines. The framework as a whole is built primarily for domain specific applications such as medical literature search for systematic reviews, or finding factually or legally applicable case law in the legal domain; however it can also be used for more general tasks. There are a number of pre-implemented components that enable common information retrieval experiments such as ad-hoc retrieval or query analysis through query performance predictors. In addition, this collection of tools seeks to be user friendly, well documented, and easily extendible. Finally, the entire pipeline can be distributed as a single binary with no dependencies, ready to use with a simple domain specific language (DSL) for constructing pipelines.

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S. Cronen-Townsend, Y. Zhou, and W. B. Croft. 2002. Predicting query performance. In SIGIR.

Digital Library

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D. Locke, G. Zuccon, and H. Scells. 2017. Automatic Query Generation from Legal Texts for Case Law Retrieval Information Retrieval Technology.

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I. Ounis, G. Amati, Plachouras V., B. He, C. Macdonald, and Johnson. 2005. Terrier Information Retrieval Platform. In ECIR.

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H. Scells, G. Zuccon, B. Koopman, A. Deacon, L. Azzopardi, and S. Geva. 2017. Integrating the framing of clinical questions via PICO into the retrieval of medical literature for systematic reviews. In CIKM'17.

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Cited By

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Bascur JVerberne Svan Eck NWaltman L(2023)Academic information retrieval using citation clusters: in-depth evaluation based on systematic reviewsScientometrics10.1007/s11192-023-04681-x128:5(2895-2921)Online publication date: 21-Mar-2023
https://doi.org/10.1007/s11192-023-04681-x
Scells HZuccon GKoopman B(2020)You Can Teach an Old Dog New Tricks: Rank Fusion applied to Coordination Level Matching for Ranking in Systematic ReviewsAdvances in Information Retrieval10.1007/978-3-030-45439-5_27(399-414)Online publication date: 8-Apr-2020
https://doi.org/10.1007/978-3-030-45439-5_27
Scells HZuccon GKoopman BClark J(2020)A Computational Approach for Objectively Derived Systematic Review Search StrategiesAdvances in Information Retrieval10.1007/978-3-030-45439-5_26(385-398)Online publication date: 8-Apr-2020
https://doi.org/10.1007/978-3-030-45439-5_26
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Index Terms

An Information Retrieval Experiment Framework for Domain Specific Applications
1. Information systems
  1. Information retrieval
    1. Specialized information retrieval
2. Software and its engineering
  1. Software notations and tools
    1. Context specific languages
      1. Domain specific languages

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Information & Contributors

Information

Published In

SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval

June 2018

1509 pages

ISBN:9781450356572

DOI:10.1145/3209978

General Chairs:
Kevyn Collins-Thompson
University of Michigan, United States
,
Qiaozhu Mei
University of Michigan, United States
,
Program Chairs:
Brian Davison
Lehigh University, United States
,
Yiqun Liu
Tsinghua University, China
,
Emine Yilmaz
University College London, United Kingdom

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 June 2018

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SIGIR '18

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SIGIR

SIGIR '18: The 41st International ACM SIGIR conference on research and development in Information Retrieval

July 8 - 12, 2018

MI, Ann Arbor, USA

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SIGIR '18 Paper Acceptance Rate 86 of 409 submissions, 21%;

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

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Cited By

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Bascur JVerberne Svan Eck NWaltman L(2023)Academic information retrieval using citation clusters: in-depth evaluation based on systematic reviewsScientometrics10.1007/s11192-023-04681-x128:5(2895-2921)Online publication date: 21-Mar-2023
https://doi.org/10.1007/s11192-023-04681-x
Scells HZuccon GKoopman B(2020)You Can Teach an Old Dog New Tricks: Rank Fusion applied to Coordination Level Matching for Ranking in Systematic ReviewsAdvances in Information Retrieval10.1007/978-3-030-45439-5_27(399-414)Online publication date: 8-Apr-2020
https://doi.org/10.1007/978-3-030-45439-5_27
Scells HZuccon GKoopman BClark J(2020)A Computational Approach for Objectively Derived Systematic Review Search StrategiesAdvances in Information Retrieval10.1007/978-3-030-45439-5_26(385-398)Online publication date: 8-Apr-2020
https://doi.org/10.1007/978-3-030-45439-5_26
Nguyen VKarimi SJin BPiwowarski BChevalier MGaussier EMaarek YNie JScholer F(2019)An Experimentation Platform for Precision MedicineProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331396(1357-1360)Online publication date: 18-Jul-2019
https://dl.acm.org/doi/10.1145/3331184.3331396
Russell-Rose TChamberlain JPiwowarski BChevalier MGaussier EMaarek YNie JScholer F(2019)An Open-Access Platform for Transparent and Reproducible Structured SearchingProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331394(1293-1296)Online publication date: 18-Jul-2019
https://dl.acm.org/doi/10.1145/3331184.3331394
Scells HZuccon GKoopman B(2019)Automatic Boolean Query Refinement for Systematic Review Literature SearchThe World Wide Web Conference10.1145/3308558.3313544(1646-1656)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308558.3313544
Scells HZuccon GCuzzocrea AAllan JPaton NSrivastava DAgrawal RBroder AZaki MCandan SLabrinidis ASchuster AWang H(2018)searchrefinerProceedings of the 27th ACM International Conference on Information and Knowledge Management10.1145/3269206.3269215(1939-1942)Online publication date: 17-Oct-2018
https://dl.acm.org/doi/10.1145/3269206.3269215
Scells HZuccon GCollins-Thompson KMei QDavison BLiu YYilmaz E(2018)Generating Better Queries for Systematic ReviewsThe 41st International ACM SIGIR Conference on Research & Development in Information Retrieval10.1145/3209978.3210020(475-484)Online publication date: 27-Jun-2018
https://dl.acm.org/doi/10.1145/3209978.3210020

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Domain specific information retrieval and text mining in medical document

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