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Enhancement of results in multi-relational data mining supported by templates

Grant number: 14/17817-2
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): October 01, 2014
Effective date (End): September 30, 2015
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computer Systems
Principal Investigator:Carlos Roberto Valêncio
Grantee:Guilherme Henrique Morais
Host Institution: Instituto de Biociências, Letras e Ciências Exatas (IBILCE). Universidade Estadual Paulista (UNESP). Campus de São José do Rio Preto. São José do Rio Preto , SP, Brazil

Abstract

With the increasing amount of data and the growing need to transform it into accurate and useful knowledge, the Multi-relational Data Mining process becomes essential for knowledge discovery and decision-making. The extraction of association rules is a well-established and widely applied method for Data Mining that generates a collection of rules that relate two or more attributes. However, this process often generates a big amount of rules from which only a few are relevant to the analysis. This work proposes the use of Templates, pre-defined formats for the association rules, for the enhancement of results in Multi-relational Data Mining based on the generation of a result set with fewer rules and greater relevance. The validation of the technique will be given through the application in real and synthetic public databases and the application in environments for the management of real data relate to human health, such as Work accidents, epilepsy and hepatitis, and patients with mental pathologies and chemical dependencies.

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