• DocumentCode
    3022396
  • Title

    A Spatial Clustering Algorithm Based on Spatial Topological Relations for GML Data

  • Author

    Ji, Genlin ; Miao, Jianxin ; Bao, Peiming

  • Author_Institution
    Dept. of Comput., Nanjing Normal Univ., Nanjing, China
  • Volume
    4
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    298
  • Lastpage
    301
  • Abstract
    GML is an application of XML in geographic information system, used to store spatial data. In this paper, algorithm SCTR-GML is proposed for spatial clustering in GML data. Compared with other spatial clustering algorithms, SCTR-GML clusters spatial objects based on the spatial topological relations, while the reported algorithms like DBSCAN just cluster the spatial objects that are near to each other into one cluster. The algorithm SCTR-GML firstly creates indexes for the spatial objects described by GML, computes all the topological relations including contain, intersect, adjacent, and also proposes a novel method to measure the similarity between spatial objects which needs the interaction of users. The objects in one cluster may not be near to each other, but they have similarity in the spatial topological relations. Encouraging simulation results are observed and reported. The experiment shows that SCTR-GML is effective and efficient.
  • Keywords
    XML; geographic information systems; pattern clustering; DBSCAN; SCTR-GML; XML; geographic information system; spatial clustering algorithm; spatial topological relations; Application software; Artificial intelligence; Clustering algorithms; Clustering methods; Computational intelligence; Computational modeling; Computer science education; Educational institutions; Geographic Information Systems; XML; GML; similarity measure; spatial clustering; spatial topological relations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.291
  • Filename
    5376346