research-article

A general evaluation measure for document organization tasks

Authors:

Enrique Amigó,

Felisa VerdejoAuthors Info & Claims

SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval

Pages 643 - 652

https://doi.org/10.1145/2484028.2484081

Published: 28 July 2013 Publication History

Abstract

A number of key Information Access tasks -- Document Retrieval, Clustering, Filtering, and their combinations -- can be seen as instances of a generic {\em document organization} problem that establishes priority and relatedness relationships between documents (in other words, a problem of forming and ranking clusters). As far as we know, no analysis has been made yet on the evaluation of these tasks from a global perspective. In this paper we propose two complementary evaluation measures -- Reliability and Sensitivity -- for the generic Document Organization task which are derived from a proposed set of formal constraints (properties that any suitable measure must satisfy).

In addition to be the first measures that can be applied to any mixture of ranking, clustering and filtering tasks, Reliability and Sensitivity satisfy more formal constraints than previously existing evaluation metrics for each of the subsumed tasks. Besides their formal properties, its most salient feature from an empirical point of view is their strictness: a high score according to the harmonic mean of Reliability and Sensitivity ensures a high score with any of the most popular evaluation metrics in all the Document Retrieval, Clustering and Filtering datasets used in our experiments.

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Cited By

Schumacher TLutz MSikdar SStrohmaier M(2024)Properties of Group Fairness Measures for RankingsACM Transactions on Social Computing10.1145/3674883Online publication date: 27-Aug-2024
https://dl.acm.org/doi/10.1145/3674883
Wu HZhang YMa CLyu FHe BMitra BLiu X(2024)Result Diversification in Search and Recommendation: A SurveyIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.338226236:10(5354-5373)Online publication date: Oct-2024
https://doi.org/10.1109/TKDE.2024.3382262
Giner F(2024)An Intrinsic Framework of Information Retrieval Evaluation MeasuresIntelligent Systems and Applications10.1007/978-3-031-47721-8_47(692-713)Online publication date: 10-Jan-2024
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Index Terms

A general evaluation measure for document organization tasks
1. Hardware
  1. Robustness

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cover image ACM Conferences

SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval

July 2013

1188 pages

ISBN:9781450320344

DOI:10.1145/2484028

General Chairs:
Gareth J.F. Jones
Dublin City University, Ireland
,
Páraic Sheridan
Dublin City University, Ireland
,
Program Chairs:
Diane Kelly
University of North Carolina, Chapel Hill, USA
,
Maarten de Rijke
University of Amsterdam, The Netherlands
,
Tetsuya Sakai
Microsoft Research Asia, China

Copyright © 2013 ACM.

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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SIGIR: ACM Special Interest Group on Information Retrieval

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Association for Computing Machinery

New York, NY, United States

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Published: 28 July 2013

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effectiveness measures

Qualifiers

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SIGIR '13

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SIGIR

SIGIR '13: The 36th International ACM SIGIR conference on research and development in Information Retrieval

July 28 - August 1, 2013

Dublin, Ireland

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SIGIR '13 Paper Acceptance Rate 73 of 366 submissions, 20%;

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

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Cited By

Schumacher TLutz MSikdar SStrohmaier M(2024)Properties of Group Fairness Measures for RankingsACM Transactions on Social Computing10.1145/3674883Online publication date: 27-Aug-2024
https://dl.acm.org/doi/10.1145/3674883
Wu HZhang YMa CLyu FHe BMitra BLiu X(2024)Result Diversification in Search and Recommendation: A SurveyIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.338226236:10(5354-5373)Online publication date: Oct-2024
https://doi.org/10.1109/TKDE.2024.3382262
Giner F(2024)An Intrinsic Framework of Information Retrieval Evaluation MeasuresIntelligent Systems and Applications10.1007/978-3-031-47721-8_47(692-713)Online publication date: 10-Jan-2024
https://doi.org/10.1007/978-3-031-47721-8_47
Giner F(2023)Information Retrieval Evaluation Measures Defined on Some Axiomatic Models of PreferencesACM Transactions on Information Systems10.1145/363217142:3(1-35)Online publication date: 8-Nov-2023
https://dl.acm.org/doi/10.1145/3632171
Giner FCrestani FPasi GGaussier E(2022)On the Effect of Ranking Axioms on IR Evaluation MetricsProceedings of the 2022 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3539813.3545153(13-23)Online publication date: 23-Aug-2022
https://dl.acm.org/doi/10.1145/3539813.3545153
Amigó EMizzaro SSpina DAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)Ranking InterruptusProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3532051(588-598)Online publication date: 6-Jul-2022
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Völske MBondarenko AFröbe MStein BSingh JHagen MAnand AHasibi FFang YAizawa A(2021)Towards Axiomatic Explanations for Neural Ranking ModelsProceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3471158.3472256(13-22)Online publication date: 11-Jul-2021
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Parapar JRadlinski F(2021)Towards Unified Metrics for Accuracy and Diversity for Recommender SystemsProceedings of the 15th ACM Conference on Recommender Systems10.1145/3460231.3474234(75-84)Online publication date: 13-Sep-2021
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