MithraRanking

A system for responsible ranking design

Yifan Guan, Abolfazl Asudeh, Pranav Mayuram, H. V. Jagadish, Julia Stoyanovich, Gerome Miklau, Gautam Das

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Items from a database are often ranked based on a combination of criteria. The weight given to each criterion in the combination can greatly affect the ranking produced. Often, a user may have a general sense of the relative importance of the different criteria, but beyond this may have the flexibility, within limits, to choose combinations that weigh these criteria differently with an acceptable region. We demonstrate MithraRanking, a system that helps users choose criterion weights that lead to “better” rankings in terms of having desirable properties while remaining within the acceptable region. The goodness properties we focus on are stability and fairness.

    Original languageEnglish (US)
    Title of host publicationSIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data
    PublisherAssociation for Computing Machinery
    Pages1913-1916
    Number of pages4
    ISBN (Electronic)9781450356435
    DOIs
    StatePublished - Jun 25 2019
    Event2019 International Conference on Management of Data, SIGMOD 2019 - Amsterdam, Netherlands
    Duration: Jun 30 2019Jul 5 2019

    Publication series

    NameProceedings of the ACM SIGMOD International Conference on Management of Data
    ISSN (Print)0730-8078

    Conference

    Conference2019 International Conference on Management of Data, SIGMOD 2019
    CountryNetherlands
    CityAmsterdam
    Period6/30/197/5/19

    Keywords

    • Data Ethics
    • Fairness
    • Linear Evaluators
    • Robustness
    • Stability
    • Transparency

    ASJC Scopus subject areas

    • Software
    • Information Systems

    Cite this

    Guan, Y., Asudeh, A., Mayuram, P., Jagadish, H. V., Stoyanovich, J., Miklau, G., & Das, G. (2019). MithraRanking: A system for responsible ranking design. In SIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data (pp. 1913-1916). (Proceedings of the ACM SIGMOD International Conference on Management of Data). Association for Computing Machinery. https://doi.org/10.1145/3299869.3320244

    MithraRanking : A system for responsible ranking design. / Guan, Yifan; Asudeh, Abolfazl; Mayuram, Pranav; Jagadish, H. V.; Stoyanovich, Julia; Miklau, Gerome; Das, Gautam.

    SIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data. Association for Computing Machinery, 2019. p. 1913-1916 (Proceedings of the ACM SIGMOD International Conference on Management of Data).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Guan, Y, Asudeh, A, Mayuram, P, Jagadish, HV, Stoyanovich, J, Miklau, G & Das, G 2019, MithraRanking: A system for responsible ranking design. in SIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data. Proceedings of the ACM SIGMOD International Conference on Management of Data, Association for Computing Machinery, pp. 1913-1916, 2019 International Conference on Management of Data, SIGMOD 2019, Amsterdam, Netherlands, 6/30/19. https://doi.org/10.1145/3299869.3320244
    Guan Y, Asudeh A, Mayuram P, Jagadish HV, Stoyanovich J, Miklau G et al. MithraRanking: A system for responsible ranking design. In SIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data. Association for Computing Machinery. 2019. p. 1913-1916. (Proceedings of the ACM SIGMOD International Conference on Management of Data). https://doi.org/10.1145/3299869.3320244
    Guan, Yifan ; Asudeh, Abolfazl ; Mayuram, Pranav ; Jagadish, H. V. ; Stoyanovich, Julia ; Miklau, Gerome ; Das, Gautam. / MithraRanking : A system for responsible ranking design. SIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data. Association for Computing Machinery, 2019. pp. 1913-1916 (Proceedings of the ACM SIGMOD International Conference on Management of Data).
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