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Constrained colocation mining: application to soil erosion characterization

Published: 22 March 2010 Publication History

Abstract

Spatial data mining has been extensively studied for GIS applications. To deal with a fast increasing of data, investigations for spatial data analysis are needed. In this paper, we propose a spatial data mining approach which adapts the existing colocation concept to characterize soil erosion hazard. In order to manage this task, we put the colocation mining task into a more general framework. Based on this framework, new constraints linked to domain knowledge are pushed into the colocation mining algorithm. Finally, we developed a prototype and lead experiments on real scientific datasets.

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Cited By

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  • (2019)A framework for generating condensed co-location sets from spatial databasesIntelligent Data Analysis10.3233/IDA-17375223:2(333-355)Online publication date: 4-Apr-2019
  • (2019)Parallel co-location mining with MapReduce and NoSQL systemsKnowledge and Information Systems10.1007/s10115-019-01381-yOnline publication date: 21-Aug-2019

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  1. Constrained colocation mining: application to soil erosion characterization

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    cover image ACM Conferences
    SAC '10: Proceedings of the 2010 ACM Symposium on Applied Computing
    March 2010
    2712 pages
    ISBN:9781605586397
    DOI:10.1145/1774088
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    Published: 22 March 2010

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    Author Tags

    1. constraint-based colocation mining
    2. domain-driven data mining
    3. soil erosion
    4. spatial data mining
    5. spatial pattern mining

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    March 22 - 26, 2010
    Sierre, Switzerland

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    SAC '10 Paper Acceptance Rate 364 of 1,353 submissions, 27%;
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    View all
    • (2019)A framework for generating condensed co-location sets from spatial databasesIntelligent Data Analysis10.3233/IDA-17375223:2(333-355)Online publication date: 4-Apr-2019
    • (2019)Parallel co-location mining with MapReduce and NoSQL systemsKnowledge and Information Systems10.1007/s10115-019-01381-yOnline publication date: 21-Aug-2019

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