• DocumentCode
    1668087
  • Title

    SNN Neighbor and SNN Density-based co-location pattern discovery

  • Author

    Zeng-fang, Yang ; He-wen, Tang

  • Author_Institution
    Department of Computer Science and Engineering, Yuxi Normal University Yuxi 653100, P.R. China
  • fYear
    2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Concerning co-location pattern mining research, the definition of co-location instance in classical algorithms is clique-based. Considering the drawbacks of this definition, this work proposes a novel definition: SNN Neighbor and SNN Density-based co-location instance. Then the paper illustrates the significance of this conception and a SNN Neighbor and SNN Density-based co-location pattern mining algorithm is realized. At last, a plenty of experimental results on synthetic and real data sets show this approach is correct and flexible, and can discovery more interesting patterns that clique-based methods fail to. Further more, our solution is faster and takes less memory consumption than traditional approaches.
  • Keywords
    Computer science; Conferences; Data mining; Electronic mail; Geographic Information Systems; Spatial databases; Telecommunications; SNN Density; SNN Neighbor; co-location instance; co-location pattern;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E -Business and E -Government (ICEE), 2011 International Conference on
  • Conference_Location
    Shanghai, China
  • Print_ISBN
    978-1-4244-8691-5
  • Type

    conf

  • DOI
    10.1109/ICEBEG.2011.5885287
  • Filename
    5885287