article · 2007

Database Mining in Spatial Databases

D. A. Bell, S.S. Anand, C. M. Shapcott

Cited by 0Abstract and details only

Abstract

The past few years has seen an explosion in the amount of data stored in databases. Apart from textual data, there has been an increase in the amount of pictorial information being stored on computers. Within this data is a lot of implicit, potentially useful information that cannot be extracted manually, simply because of the size of the data and the scarcity of human resources. Thus, the need for automated discovery tools is clear and a lot of effort is being devoted to building such tools. In this paper we present a method for discovery in spatial databases. A general framework for databases mining in relational databases based on evidential theory [ANAN93] is extended to incorporate spatial discovery. We discuss the role of the Dempster-Shafer orthogonal sum combination rule in such a framework. Keywords : Database Mining, Spatial Reasoning, Evidential Theory, Dempster-Shafer Orthogonal Sum. 1. Introduction The discovery of knowledge can come about in many ways. Various modes of d...

Cite this paper

APA 7

Bell, D. A., Anand, S., & Shapcott, C. M. (2007). Database Mining in Spatial Databases.

MLA 9

Bell, D. A., et al. “Database Mining in Spatial Databases.” 2007.

Chicago

Bell, D. A., S.S. Anand, and C. M. Shapcott. 2007. “Database Mining in Spatial Databases.”

Harvard

Bell, D.A., Anand, S. and Shapcott, C.M. (2007) ‘Database Mining in Spatial Databases’.

BibTeX

@article{bell2007database,
  title = {{Database Mining in Spatial Databases}},
  author = {Bell, D. A. and Anand, S.S. and Shapcott, C. M.},
  year = {2007}
}

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