Recent Trends in Spatial Data Mining and Its Challenges

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Author(s): Anuradha Jagadeesan (VIT University, India), Prathik A (VIT University, India)and Tripathy B K (VIT University, India)
Copyright: 2016
Pages: 18
Source title: Handbook of Research on Computational Intelligence Applications in Bioinformatics
Source Author(s)/Editor(s): Sujata Dash (North Orissa University, India)and Bidyadhar Subudhi (National Institute of Technology, India)
DOI: 10.4018/978-1-5225-0427-6.ch003

Keywords: Artificial Intelligence / Bioinformatics / Computer Science & IT / Medical Information Science Reference

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Abstract

With tremendous development in the field of science and technology, there is vast amount of data which are used in analytics for decision making. Considering its spatial characteristics for mining will enhance the accuracy of decision. So, obtaining knowledge from spatial data becomes very essential and meaningful. The spatial database contains very numerous amounts of spatial and non-spatial data of different forms. Interpretation and analyzing of vast data is far beyond human ability. In order to acquire knowledge on such scenario we need spatial data mining. The challenges involved in spatial mining are to deal with different objects that represent the spatial characteristics. This makes spatial data mining a dominant research field. This chapter briefs about the characteristics of spatial data mining and the methods of spatial data mining in recent years.

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Recent Trends in Spatial Data Mining and Its Challenges

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