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An efficient layout method for a large collection of geographic data entries

Published: 18 March 2013 Publication History
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  • Abstract

    Many spatial applications require the ability to display locations of geographic data entries on an online map. For example, an online photo-sharing service may wish to display photos (as thumbnails) according to where they were taken. Since displaying geographic data entries as thumbnails or icons on a map requires some amount of space, displayed entries can overlap each other. As a result, we may wish to discard less popular or older entries (based on a given measure of importance) so that these more popular or newer entries become more distinct. A straightforward solution is to apply a spatial database extension such as PostGIS (i) to retrieve entries within a given display window; (ii) to discard entries in proximity of a more important one. In this paper, we demonstrate our method for efficiently selecting distinct entries from a large geographical point set. Specifically, our demonstration software presents a voting system built upon an ensemble of interrelated indexes, which is the main novelty of our query processing method. This allows us to efficiently determine the degree of distinctiveness of all entries within a query window using simple index traversal operations rather than expensive spatial operations. The effectiveness of our method in comparison to a traditional spatial query is shown by our experimental results using a real dataset of over 9 million locations. These experimental results show that our proposed method is capable of consistently producing subsecond response times, while the spatial query-based method takes more than 10 seconds on average in a low spatial selectivity setting.

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    Published In

    cover image ACM Other conferences
    EDBT '13: Proceedings of the 16th International Conference on Extending Database Technology
    March 2013
    793 pages
    ISBN:9781450315975
    DOI:10.1145/2452376

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 18 March 2013

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    Author Tags

    1. query processing
    2. spatial databases

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    EDBT/ICDT '13

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    Overall Acceptance Rate 7 of 10 submissions, 70%

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