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  • Argument free clustering for large spatial point-data sets via boundary extraction from Delaunay Diagram

    Author(s)
    Estivill-Castro, V
    Lee, I
    Griffith University Author(s)
    Estivill-Castro, Vladimir
    Year published
    2002
    Metadata
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    Abstract
    Minimizing the need for user-specified arguments results in less costly Geographical Data Mining. For massive data sets, the need to find best-fit arguments in semi-automatic clustering is not the only concern, the manipulation of data to find arguments opposes the philosophy of ''let the data speak for themselves'' that underpins exploratory data analysis. Our new approach consists of effective and efficient methods for discovering cluster boundaries in point-data sets. Parameters are not specified by users. Rather, values for parameters are revealed from the proximity structures of Voronoi modeling, and thus, an algorithm, ...
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    Minimizing the need for user-specified arguments results in less costly Geographical Data Mining. For massive data sets, the need to find best-fit arguments in semi-automatic clustering is not the only concern, the manipulation of data to find arguments opposes the philosophy of ''let the data speak for themselves'' that underpins exploratory data analysis. Our new approach consists of effective and efficient methods for discovering cluster boundaries in point-data sets. Parameters are not specified by users. Rather, values for parameters are revealed from the proximity structures of Voronoi modeling, and thus, an algorithm, AUTOCLUST, calculates them from the Delunay Diagram. We detect clusters of different densities and sparse clusters near to high-density clusters. Multiple bridges linking clusters are identified and removed. All this within O(n log n) time, where n is the number of data points. We contrast AUTOCLUST with algorithms for clustering large georeferenced sets of points. These comparisons confirm the virtues of our approach.
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    Journal Title
    Computers, Environment and Urban Systems
    Volume
    26
    Issue
    4
    Publisher URI
    http://www.sciencedirect.com/science/journal/01989715
    DOI
    https://doi.org/10.1016/S0198-9715(01)00044-8
    Subject
    Geomatic engineering
    Urban and regional planning
    Publication URI
    http://hdl.handle.net/10072/22041
    Collection
    • Journal articles

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