A Novel Approach of Multilevel Positive and Negative Association Rule Mining for Spatial Databases

  • L. K. Sharma
  • O. P. Vyas
  • U. S. Tiwary
  • R. Vyas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3587)


Spatial data mining is a demanding field since huge amounts of spatial data have been collected in various applications, ranging form Remote Sensing to GIS, Computer Cartography, Environmental Assessment and Planning. Although there have been efforts for spatial association rule mining, but mostly researchers discuss only the positive spatial association rules; they have not considered the spatial negative association rules. Negative association rules are very useful in some spatial problems and are capable of extracting some useful and previously unknown hidden information. We have proposed a novel approach of mining spatial positive and negative association rules. The approach applies multiple level spatial mining methods to extract interesting patterns in spatial and/or non-spatial predicates. Data and spatial predicates/association-ship are organized as set hierarchies to mine them level-by-level as required for multilevel spatial positive and negative association rules. A pruning strategy is used in our approach to efficiently reduce the search space. Further efficiency is gained by interestingness measure.


Association Rule Spatial Database Association Rule Mining Spatial Object Pruning Strategy 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • L. K. Sharma
    • 1
  • O. P. Vyas
    • 1
  • U. S. Tiwary
    • 2
  • R. Vyas
    • 1
  1. 1.School of Studies in Computer SciencePt. Ravishankar Shukla UniversityRaipurIndia
  2. 2.Indian Institute of Information TechnologyAllahabadIndia

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