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  • Answering Why-Not Group Spatial Keyword Queries

    Author(s)
    Zheng, Bolong
    Zheng, Kai
    Jensen, Christian S
    Nguyen, Quoc Viet Hung
    Su, Han
    Li, Guohui
    Zhou, Xiaofang
    Griffith University Author(s)
    Nguyen, Henry
    Year published
    2019
    Metadata
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    Abstract
    With the proliferation of geo-textual objects on the web, extensive efforts have been devoted to improving the efficiency of top-k spatial keyword queries in different settings. However, comparatively much less work has been reported on enhancing the quality and usability of such queries. In this context, we propose means of enhancing the usability of a top-k group spatial keyword query, where a group of users aim to find k objects that contain given query keywords and are nearest to the users. Specifically, when users receive the result of such a query, they may find that one or more objects that they expect to be in the ...
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    With the proliferation of geo-textual objects on the web, extensive efforts have been devoted to improving the efficiency of top-k spatial keyword queries in different settings. However, comparatively much less work has been reported on enhancing the quality and usability of such queries. In this context, we propose means of enhancing the usability of a top-k group spatial keyword query, where a group of users aim to find k objects that contain given query keywords and are nearest to the users. Specifically, when users receive the result of such a query, they may find that one or more objects that they expect to be in the result are in fact missing, and they may wonder why. To address this situation, we develop a so-called why-not query that is able to minimally modify the original query into a query that returns the expected, but missing, objects, in addition to other objects. Specifically, we formalize the why-not query in relation to the top-k group spatial keyword query, called the Why-not Group Spatial Keyword Query (WGSK) that is able to provide a group of users with a more satisfactory query result. We propose a three-phase framework for efficiently computing he WGSK. Extensive experiments with real and synthetic data offer evidence that the proposed solution excels over baselines with respect to both effectiveness and efficiency.
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    Conference Title
    2019 IEEE 35th International Conference on Data Engineering (ICDE)
    DOI
    https://doi.org/10.1109/ICDE.2019.00272
    Subject
    Distributed computing and systems software
    Science & Technology
    Computer Science, Information Systems
    Publication URI
    http://hdl.handle.net/10072/392466
    Collection
    • Conference outputs

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