Scholarship 15/08059-0 - Mineração de dados, Agrupamento de dados - BV FAPESP
Advanced search
Start date
Betweenand

Exploration of association rules clustering through objective measures

Grant number: 15/08059-0
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Start date until: July 01, 2015
End date until: June 30, 2016
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Veronica Oliveira de Carvalho
Grantee:Davi Duarte de Paula
Host Institution: Instituto de Geociências e Ciências Exatas (IGCE). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil

Abstract

Many objective evaluation measures (OMs) have been proposed in the last years as a mean of post-processing association rules. Therefore, the first challenge during an exploration process is to decide which OM to use. For that, one can: (a) reduce the number of OMs to be chosen; (b) aggregate OMs' values in one importance's value as a mean of not selecting a suitable OM. The problem with (a) is that many OMs can remain. Regarding (b), an optimal equation, that derives a single value, is generally obtained, which cannot be well understandable by the user. In this context, [Carvalho et al., 2015] propose a process to cluster association rules, based on the existing similarity among the rankings obtained by a set of OMs, in order to direct the user to the interesting patterns of the domain. The idea is to solve the problem related to the identification of a set of suitable OMs, by implicit combining OMs, without using any optimization method. Therefore, with this process (I) it is not necessary to select a set of suitable OMs nor explicit aggregate many OMs, in order to rank the rules to find the interesting ones; (II) the exploration space can be reduced since it is considered that there is a subset of groups that contains all the interesting rules, so that a small number of groups have to be explored. However, the described process presents some gaps to be explored.Based on the exposed, this project aims to improve the process proposed by [Carvalho et al., 2015] in order to: (a) explore ways to rank the clusters so that the user can explore only the n first groups (the ones that will contain the interesting patterns); (b) explore alternative ways to rank the rules inside the clusters to try to improve the results; (c) explore the results of the process when the OMs used in the clustering are redundant (i.e., lead to the same ranking).

News published in Agência FAPESP Newsletter about the scholarship:
More itemsLess items
Articles published in other media outlets ( ):
More itemsLess items
VEICULO: TITULO (DATA)
VEICULO: TITULO (DATA)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
DE CARVALHO, VERONICA OLIVEIRA; DE PAULA, DAVI DUARTE; PACHECO, MATEUS VIOLANTE; DOS SANTOS, WALDEILSON EDER; DE PADUA, RENAN; REZENDE, SOLANGE OLIVEIRA; CASTRO, F; MIRANDAJIMENEZ, S; GONZALEZMENDOZA, M. Ranking Association Rules by Clustering Through Interestingness. ADVANCES IN SOFT COMPUTING, MICAI 2017, PT I, v. 10632, p. 16-pg., . (15/08059-0)

Please report errors in scientific publications list using this form.