Mining geo-referenced databases: a way to improve decision-making

Knowledge discovery in databases is a process that aims at the discovery of associations within data sets. The analysis of geo-referenced data demands a particular approach in this process. This chapter presents a new approach to the process of knowledge discovery, in which qualitative geographic id...

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Bibliographic Details
Main Author: Santos, Maribel Yasmina (author)
Other Authors: Amaral, Luís (author)
Format: bookPart
Language:eng
Published: 2005
Subjects:
Online Access:http://hdl.handle.net/1822/1353
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/1353
Description
Summary:Knowledge discovery in databases is a process that aims at the discovery of associations within data sets. The analysis of geo-referenced data demands a particular approach in this process. This chapter presents a new approach to the process of knowledge discovery, in which qualitative geographic identifiers give the positional aspects of geographic data. Those identifiers are manipulated using qualitative reasoning principles, which allows for the inference of new spatial relations required for the data mining step of the knowledge discovery process. The efficacy and usefulness of the implemented system — PADRÃO — has been tested with a bank dataset. The results obtained support that traditional knowledge discovery systems, developed for relational databases and not having semantic knowledge linked to spatial data, can be used in the process of knowledge discovery in geo-referenced databases, since some of this semantic knowledge and the principles of qualitative spatial reasoning are available as spatial domain knowledge.