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Query quality: user ratings and system predictions

Published: 19 July 2010 Publication History

Abstract

Numerous studies have examined the ability of query performance prediction methods to estimate a query's quality for system effectiveness measures (such as average precision). However, little work has explored the relationship between these methods and user ratings of query quality. In this poster, we report the findings from an empirical study conducted on the TREC ClueWeb09 corpus, where we compared and contrasted user ratings of query quality against a range of query performance prediction methods. Given a set of queries, it is shown that user ratings of query quality correlate to both system effectiveness measures and a number of pre-retrieval predictors.

References

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A. Turpin and W. Hersh. Do clarity scores for queries correlate with user performance? In ADC '04, pages 85--91, 2004.
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Y. Zhao and F. Scholer. Predicting query performance for user-based search tasks. In ADC '07, pages 112--115, 2007.
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Y. Zhao, F. Scholer, and Y. Tsegay. Effective pre-retrieval query performance prediction using similarity and variability evidence. In ECIR '08, pages 52--64, 2008.
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Cited By

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  • (2018)An analysis of evaluation campaigns in ad-hoc medical information retrieval: CLEF eHealth 2013 and 2014Information Retrieval Journal10.1007/s10791-018-9331-421:6(507-540)Online publication date: 3-May-2018
  • (2016)Rethinking the Cost of Information Search BehaviorProceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval10.1145/2911451.2914742(969-972)Online publication date: 7-Jul-2016
  • (2015)Diversity-Aware Top-k Publish/Subscribe for Text StreamProceedings of the 2015 ACM SIGMOD International Conference on Management of Data10.1145/2723372.2749451(347-362)Online publication date: 27-May-2015
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  1. Query quality: user ratings and system predictions

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    cover image ACM Conferences
    SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
    July 2010
    944 pages
    ISBN:9781450301534
    DOI:10.1145/1835449
    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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    Publication History

    Published: 19 July 2010

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    1. query performance prediction

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    SIGIR '10 Paper Acceptance Rate 87 of 520 submissions, 17%;
    Overall Acceptance Rate 792 of 3,983 submissions, 20%

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    View all
    • (2018)An analysis of evaluation campaigns in ad-hoc medical information retrieval: CLEF eHealth 2013 and 2014Information Retrieval Journal10.1007/s10791-018-9331-421:6(507-540)Online publication date: 3-May-2018
    • (2016)Rethinking the Cost of Information Search BehaviorProceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval10.1145/2911451.2914742(969-972)Online publication date: 7-Jul-2016
    • (2015)Diversity-Aware Top-k Publish/Subscribe for Text StreamProceedings of the 2015 ACM SIGMOD International Conference on Management of Data10.1145/2723372.2749451(347-362)Online publication date: 27-May-2015
    • (2015)Proceedings of the 2015 ACM SIGMOD International Conference on Management of DataundefinedOnline publication date: 27-May-2015
    • (2014)An analysis of query difficulty for information retrieval in the medical domainProceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval10.1145/2600428.2609496(1007-1010)Online publication date: 3-Jul-2014
    • (2012)User evaluation of query qualityProceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval10.1145/2348283.2348315(215-224)Online publication date: 12-Aug-2012

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