• DocumentCode
    441806
  • Title

    Qualitative spatial relationships cleaning for spatial data mining

  • Author

    Sun, Hai-Bin ; Li, Wen-Hui

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
  • Volume
    3
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    1851
  • Abstract
    In this article, we investigate the problem of preparing qualitative spatial relations before implementing spatial data mining by checking consistency in a constraint network, which includes topological and cardinal directional relations between pairs of spatial objects. We aim to explore potential spatial relations and possible inconsistency among the data of relationships for enforcing the correctness of spatial data mining. This task is carried out through qualitative spatial reasoning method, specifically consistency checking. We try to lay the theoretical foundation for this kind of problem. Instead of using conventional composition tables, we investigate the interactions between topological and cardinal directional relations with the aid of rules. These rules are shown to be sound, i.e. the deductions are logically correct. Based on these rules, an improved constraint propagation algorithm is introduced to enforce the path consistency. An example is presented to show the utility of these rules.
  • Keywords
    computational complexity; constraint handling; data integrity; data mining; relational databases; spatial data structures; spatial reasoning; visual databases; cardinal directional relations; computational complexity; consistency checking; constraint network; constraint propagation; path consistency; qualitative spatial relationship cleaning; spatial data mining; spatial objects; spatial relations; topological directional relations; Cleaning; Computational complexity; Computer networks; Computer science education; Data mining; Knowledge engineering; Laboratories; Spatial databases; Sun; Topology; Qualitative spatial reasoning; computational complexity; consistency checking; spatial data mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527247
  • Filename
    1527247