Fast Identification of Interesting Spatial Regions with Applications in Human Development Research

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    Large-scale demographic datasets with spatial information provide a rich platform for human development research. Much emphasis is often placed on understanding deviations from dataset-level behavior across demographic attributes within spatially coherent regions, since those could point to a local condition worth addressing through regional policies, or at the other extreme, a less known success story that offers new learnings. Inspired by such scenarios, we build upon domain knowledge from HDR to devise an interestingness scoring for spatial regions and formulate the computational task of interesting spatial region identification. Accordingly, we develop a taxonomic organization of spatial regions and formulate bounds on interestingness scores, which are then leveraged to develop an efficient technique to address the task. Our search method is empirically evaluated over two real-world datasets, and is seen to record orders of magnitude of response time improvements over region enumeration. The absolute response times and the memory overheads of our approach are seen to be within highly desirable ranges, establishing the effectiveness of our solution for the task.

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    • Fast Identification of Interesting Spatial Regions with Applications in Human Development Research

      Rights statement: © 2018 Springer Verlag. This work is made available online in accordance with the publisher’s policies. Please refer to any applicable terms of use of the publisher.

      Accepted author manuscript, 283 KB, PDF-document

      Embargo ends: 09/08/2019

    DOI

    Original languageEnglish
    Title of host publication International Conference on Database and Expert Systems Applications: Proceedings
    PublisherSpringer
    Pages408-416
    Number of pages9
    DOIs
    Publication statusPublished - 09 Aug 2018
    EventInternational Conference on Database and Expert Systems Applications - Regensburg, Regensburg, Germany
    Duration: 03 Sep 201806 Sep 2018
    Conference number: 29
    http://www.dexa.org/dexa2018

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag
    Volume11030
    ISSN (Print)0302-9743

    Conference

    ConferenceInternational Conference on Database and Expert Systems Applications
    Abbreviated titleDEXA 2018
    CountryGermany
    CityRegensburg
    Period03/09/201806/09/2018
    Internet address

    ID: 153973477