Research of Local Co-location Pattern in Spatial Event Sequences

  • Wang Zhanquan
  • Yu Huiqun
  • Chen Haibo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4223)


The present works are focusing on the discovery of global co-location patterns. It is a challenging problem to find the local co-location patterns. A novel method was presented to find local co-location patterns in an event sequence. The local co-location patterns were found by using an effective multi-layer index in a given time window (win) and local neighbor domain set. The experiment was done to prove algorithm effective and feasible.


Spatial Feature Event Sequence Spatial Database Frequent Item Spatial Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Agarwal, R., Srikant, R.: Fast Algorithms for Mining Association Rules. In: Proc. 20th Int. VLDB, Santiago, Chile, September 12-15, pp. 487–499 (1994)Google Scholar
  2. 2.
    Huang, Y.: Mining Co-Location Patterns from Large Spatial Datasets, PhD dissertation of the University of Minnesota (2003)Google Scholar
  3. 3.
    Chawla, S., Sekhar, S., Wu, W., Ozesmi, U.: Extending Data Mining for Spatial Applications A Case Study in Predicting Nest Locations. In: Conf. on ACM SIGMOD (2000)Google Scholar
  4. 4.
    Guting, R.H.: An introduction to Spatial Database Systems. In: VLDBJ (1994)Google Scholar
  5. 5.
    Koperski, K., Han, J.W.: Discovery of Spatial Association Rules in Geographic Information Database. In: Proc. 4th Int. Large Spatial Database, Maine, August 1995, pp. 47–66 (1995)Google Scholar
  6. 6.
    Morimoto, Y.: Mining Frequent Neighboring Class Sets in Spatial Databases. In: Proc. 7th int. Knowledge discovery and data mining, San Francisco, California, pp. 353–358 (2001)Google Scholar
  7. 7.
    Shekhar, S., Huang, Y.: Discovering Spatial Co-location Patterns: A Summary of Results. In: Proc. 7th Int. Spatial and Temporal Databases, Redondo Beach, CA, USA, pp. 236–256 (2001)Google Scholar
  8. 8.
    Wang, Z.Q.: Spatial Co-location Rule Mining Algorithm in Categorical Data. Journal of Computer-aided Design & Computer Graphics 17(10), 320–327 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wang Zhanquan
    • 1
  • Yu Huiqun
    • 1
  • Chen Haibo
    • 2
  1. 1.Department of Computer Science and EngineeringEast China University of Science and TechnologyShanghaiChina
  2. 2.College of ScienceZhejiang Sci-tech UniversityHangzhouChina

Personalised recommendations