skip to main content
10.1145/2348283.2348519acmconferencesArticle/Chapter ViewAbstractPublication PagesirConference Proceedingsconference-collections
poster

Unsupervised linear score normalization revisited

Published: 12 August 2012 Publication History

Abstract

We give a fresh look into score normalization for merging result-lists, isolating the problem from other components. We focus on three of the simplest, practical, and widely-used linear methods which do not require any training data, i.e. MinMax, Sum, and Z-Score. We provide theoretical arguments on why and when the methods work, and evaluate them experimentally. We find that MinMax is the most robust under many circumstances, and that Sum is - in contrast to previous literature - the worst. Based on the insights gained, we propose another three simple methods which work as good or better than the baselines.

References

[1]
A. Arampatzis and J. Kamps. A signal-to-noise approach to score normalization. In Proceeding of the ACM CIKM, pages 797--806, 2009.
[2]
J. Arguello, J. Callan, and F. Diaz. Classification-based resource selection. In Proceedings of the ACM CIKM, pages 1277--1286. ACM, 2009.
[3]
J. H. Lee. Analyses of multiple evidence combination. In Proceedings of the ACM SIGIR, pages 267--276. ACM, 1997.
[4]
R. Manmatha and H. Sever. A formal approach to score normalization for meta-search. In Proceedings of the HLT, pages 98--103. MKP Inc., 2002.
[5]
M. Montague and J. A. Aslam. Relevance score normalization for metasearch. In Proceedings of the ACM CIKM, pages 427--433. ACM, 2001.

Cited By

View all
  • (2024)Wise Fusion: Group Fairness Enhanced Rank FusionProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679649(163-174)Online publication date: 21-Oct-2024
  • (2021)Machine Learning in Preoperative Prediction of Postoperative Immediate Remission of Histology-Positive Cushing’s DiseaseFrontiers in Endocrinology10.3389/fendo.2021.63579512Online publication date: 2-Mar-2021
  • (2019)Evaluation of Suitable Amount of Water and Fertilizer for Mature Grapes in Drip Irrigation in Extreme Arid RegionsSustainability10.3390/su1107206311:7(2063)Online publication date: 7-Apr-2019
  • Show More Cited By

Index Terms

  1. Unsupervised linear score normalization revisited

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
    August 2012
    1236 pages
    ISBN:9781450314725
    DOI:10.1145/2348283

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 12 August 2012

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. distributed retrieval
    2. score normalization

    Qualifiers

    • Poster

    Conference

    SIGIR '12
    Sponsor:

    Acceptance Rates

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

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)5
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 23 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Wise Fusion: Group Fairness Enhanced Rank FusionProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679649(163-174)Online publication date: 21-Oct-2024
    • (2021)Machine Learning in Preoperative Prediction of Postoperative Immediate Remission of Histology-Positive Cushing’s DiseaseFrontiers in Endocrinology10.3389/fendo.2021.63579512Online publication date: 2-Mar-2021
    • (2019)Evaluation of Suitable Amount of Water and Fertilizer for Mature Grapes in Drip Irrigation in Extreme Arid RegionsSustainability10.3390/su1107206311:7(2063)Online publication date: 7-Apr-2019
    • (2018)Fusion in Information RetrievalThe 41st International ACM SIGIR Conference on Research & Development in Information Retrieval10.1145/3209978.3210186(1383-1386)Online publication date: 27-Jun-2018
    • (2016)A Probabilistic Fusion FrameworkProceedings of the 25th ACM International on Conference on Information and Knowledge Management10.1145/2983323.2983739(1463-1472)Online publication date: 24-Oct-2016
    • (2015)Distributed Information Retrieval: Developments and StrategiesInternational Journal of Engineering Research in Africa10.4028/www.scientific.net/JERA.16.11016(110-144)Online publication date: Jun-2015
    • (2015)Improving Concept-Based Image Retrieval with Training Weights Computed from TagsACM Transactions on Multimedia Computing, Communications, and Applications10.1145/279023012:2(1-22)Online publication date: 2-Nov-2015
    • (2014)Utilizing relevance feedback in fusion-based retrievalProceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval10.1145/2600428.2609573(313-322)Online publication date: 3-Jul-2014
    • (2013)On CORI results mergingProceedings of the 35th European conference on Advances in Information Retrieval10.1007/978-3-642-36973-5_76(752-755)Online publication date: 24-Mar-2013
    • (2013)Distributed information retrieval and applicationsProceedings of the 35th European conference on Advances in Information Retrieval10.1007/978-3-642-36973-5_104(865-868)Online publication date: 24-Mar-2013

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media