Reducing False Discoveries in Statistically-Significant Regional-Colocation Mining: A Summary of Results

Subhankar Ghosh, Jayant Gupta, Arun Sharma, Shuai An, Shashi Shekhar

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

    Abstract

    Given a set S of spatial feature types, its feature instances, a study area, and a neighbor relationship, the goal is to find pairs <a region (rg), a subset C of S> such that C is a statistically significant regional-colocation pattern in rg. This problem is important for applications in various domains including ecology, economics, and sociology. The problem is computationally challenging due to the exponential number of regional colocation patterns and candidate regions. Previously, we proposed a miner [8] that finds statistically significant regional colocation patterns. However, the numerous simultaneous statistical inferences raise the risk of false discoveries (also known as the multiple comparisons problem) and carry a high computational cost. We propose a novel algorithm, namely, multiple comparisons regional colocation miner (MultComp-RCM) which uses a Bonferroni correction. Theoretical analysis, experimental evaluation, and case study results show that the proposed method reduces both the false discovery rate and computational cost.

    Original languageEnglish (US)
    Title of host publication12th International Conference on Geographic Information Science, GIScience 2023
    EditorsRoger Beecham, Jed A. Long, Dianna Smith, Qunshan Zhao, Sarah Wise
    PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
    ISBN (Electronic)9783959772884
    DOIs
    StatePublished - Sep 2023
    Event12th International Conference on Geographic Information Science, GIScience 2023 - Leeds, United Kingdom
    Duration: Sep 12 2023Sep 15 2023

    Publication series

    NameLeibniz International Proceedings in Informatics, LIPIcs
    Volume277
    ISSN (Print)1868-8969

    Conference

    Conference12th International Conference on Geographic Information Science, GIScience 2023
    Country/TerritoryUnited Kingdom
    CityLeeds
    Period9/12/239/15/23

    Bibliographical note

    Publisher Copyright:
    © Subhankar Ghosh, Jayant Gupta, Arun Sharma, Shuai An, and Shashi Shekhar.

    Keywords

    • Colocation pattern
    • Multiple comparisons problem
    • Participation index
    • Spatial heterogeneity
    • Statistical significance

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