research-article

Comparing citation contexts for information retrieval

Authors:

Stephen Robertson,

Simone TeufelAuthors Info & Claims

CIKM '08: Proceedings of the 17th ACM conference on Information and knowledge management

Pages 213 - 222

https://doi.org/10.1145/1458082.1458113

Published: 26 October 2008 Publication History

Abstract

In previous work, we have shown that using terms from around citations in citing papers to index the cited paper, in addition to the cited paper's own terms, can improve retrieval effectiveness. Now, we investigate how to select text from around the citations in order to extract good index terms. We compare the retrieval effectiveness that results from a range of contexts around the citations, including no context, the entire citing paper, some fixed windows and several variations with linguistic motivations. We conclude with an analysis of the benefits of more complex, linguistically motivated methods for extracting citation index terms, over using a fixed window of terms. We speculate that there might be some advantage to using computational linguistic techniques for this task.

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Cited By

Wang JBansal KArapakis IGe XJose J(2024)Empowering Legal Citation Recommendation via Efficient Instruction-Tuning of Pre-trained Language ModelsAdvances in Information Retrieval10.1007/978-3-031-56027-9_19(310-324)Online publication date: 20-Mar-2024
https://doi.org/10.1007/978-3-031-56027-9_19
Heibi IPeroni S(2022)A quantitative and qualitative open citation analysis of retracted articles in the humanitiesQuantitative Science Studies10.1162/qss_a_002223:4(953-975)Online publication date: 20-Dec-2022
https://doi.org/10.1162/qss_a_00222
Iqbal SSafder IAljohani NAlfakeeh AVisvizi ANawaz RHassan S(2022)Who Cites Whom and How It Impacts the Knowledge Production Process across Disciplines?: A Methodological InsightScience & Technology Libraries10.1080/0194262X.2022.2059607(1-14)Online publication date: 13-Apr-2022
https://doi.org/10.1080/0194262X.2022.2059607
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Index Terms

Comparing citation contexts for information retrieval
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems
  1. Information retrieval
    1. Document representation
      1. Content analysis and feature selection

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cover image ACM Conferences

CIKM '08: Proceedings of the 17th ACM conference on Information and knowledge management

October 2008

1562 pages

ISBN:9781595939913

DOI:10.1145/1458082

General Chair:
James G. Shanahan
Church and Duncan Group Inc, USA
,
Program Chairs:
Sihem Amer-Yahia
Yahoo! Research, USA
,
Ioana Manolescu
INRIA, France
,
Yi Zhang
University of California, Santa Cruz, USA
,
David A. Evans
JustSystems Evans Research, USA
,
Alek Kolcz
Microsoft Live Labs, USA
,
Key-Sun Choi
KAIST, Korea
,
Abdur Chowdury
Twitter, USA

Copyright © 2008 ACM.

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Published: 26 October 2008

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Cited By

Wang JBansal KArapakis IGe XJose J(2024)Empowering Legal Citation Recommendation via Efficient Instruction-Tuning of Pre-trained Language ModelsAdvances in Information Retrieval10.1007/978-3-031-56027-9_19(310-324)Online publication date: 20-Mar-2024
https://doi.org/10.1007/978-3-031-56027-9_19
Heibi IPeroni S(2022)A quantitative and qualitative open citation analysis of retracted articles in the humanitiesQuantitative Science Studies10.1162/qss_a_002223:4(953-975)Online publication date: 20-Dec-2022
https://doi.org/10.1162/qss_a_00222
Iqbal SSafder IAljohani NAlfakeeh AVisvizi ANawaz RHassan S(2022)Who Cites Whom and How It Impacts the Knowledge Production Process across Disciplines?: A Methodological InsightScience & Technology Libraries10.1080/0194262X.2022.2059607(1-14)Online publication date: 13-Apr-2022
https://doi.org/10.1080/0194262X.2022.2059607
Asubiaro TAjiferuke I(2022)Semantic similarity-based credit attribution on citation paths: a method for allocating residual citation to and investigating depth of influence of scientific communicationsScientometrics10.1007/s11192-022-04522-3127:11(6257-6277)Online publication date: 28-Sep-2022
https://doi.org/10.1007/s11192-022-04522-3
Wang SMao JCao YLi G(2022)Integrated knowledge content in an interdisciplinary field: identification, classification, and applicationScientometrics10.1007/s11192-022-04282-0127:11(6581-6614)Online publication date: 14-Feb-2022
https://doi.org/10.1007/s11192-022-04282-0
Huang ZLow CTeng MZhang HHo DKrass MGrabmair MMaranhão JWyner A(2021)Context-aware legal citation recommendation using deep learningProceedings of the Eighteenth International Conference on Artificial Intelligence and Law10.1145/3462757.3466066(79-88)Online publication date: 21-Jun-2021
https://dl.acm.org/doi/10.1145/3462757.3466066
Rüdiger MAntons DSalge T(2021)The explanatory power of citations: a new approach to unpacking impact in scienceScientometrics10.1007/s11192-021-04103-w126:12(9779-9809)Online publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1007/s11192-021-04103-w
Heibi IPeroni S(2021)A qualitative and quantitative analysis of open citations to retracted articles: the Wakefield 1998 et al.'s caseScientometrics10.1007/s11192-021-04097-5Online publication date: 5-Aug-2021
https://doi.org/10.1007/s11192-021-04097-5
Iqbal SHassan SAljohani NAlelyani SNawaz RBornmann L(2021)A decade of in-text citation analysis based on natural language processing and machine learning techniques: an overview of empirical studiesScientometrics10.1007/s11192-021-04055-1126:8(6551-6599)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1007/s11192-021-04055-1
Färber MJatowt A(2020)Citation recommendation: approaches and datasetsInternational Journal on Digital Libraries10.1007/s00799-020-00288-221:4(375-405)Online publication date: 1-Dec-2020
https://dl.acm.org/doi/10.1007/s00799-020-00288-2
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