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A survey on data mining and knowledge discovery techniques for spatial data

Author

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  • Majid Shishehgar
  • Seyed Nasirodin Mirmohammadi
  • Ahmad Reza Ghapanchi

Abstract

Spatial data in databases, specifically in geographic information systems (GIS) data centres, can produce huge amounts of data. This great volume of information includes useful and non-useful data along with some hidden patterns which can be better managed and controlled by utilising some novel artificial intelligence methods. In this research we have a brief survey on the application of statistical methods like data mining and knowledge discovery on spatial data. First, we present an overview of geospatial data mining and knowledge discovery techniques, including spatial clustering, classification, prediction, associate rules and pattern analysis. Then, some challenges faced by geographic knowledge discovery in geographic information systems (GIS) have discussed in order to have a more clear idea of the future's researches in this area.

Suggested Citation

  • Majid Shishehgar & Seyed Nasirodin Mirmohammadi & Ahmad Reza Ghapanchi, 2015. "A survey on data mining and knowledge discovery techniques for spatial data," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 19(2), pages 265-276.
    • Handle: RePEc:ids:ijbisy:v:19:y:2015:i:2:p:265-276
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    Cited by:

    1. Loureiro, Sandra Maria Correia & Guerreiro, João & Tussyadiah, Iis, 2021. "Artificial intelligence in business: State of the art and future research agenda," Journal of Business Research, Elsevier, vol. 129(C), pages 911-926.

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