DocumentCode :
3723097
Title :
A Clustering-Based Approach to the Mining of Analogical Proportions
Author :
William Correa Beltran;Helene Jaudoin;Olivier Pivert
Author_Institution :
IRISA/Shaman, Univ. of Rennes 1, Lannion, France
fYear :
2015
Firstpage :
125
Lastpage :
131
Abstract :
This paper presents an approach aimed at mining a new type of pattern in data, namely analogical proportions. An analogical proportion expresses the equality of the relationships between the attributes of two pairs of structured objects. This notion is investigated in the database context for the discovery of different forms of "parallels" between pairs of tuples. First, we give a formal definition of the analogical proportion in the setting of relational databases. Then we focus on the problem of mining analogical proportions. We propose to use a clustering approach for enumerating parallels occurring in a relation, thus discovering analogical proportions.
Keywords :
"Data mining","Relational databases","Distortion","Animals","Connectors","Market research"
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2015 IEEE 27th International Conference on
ISSN :
1082-3409
Type :
conf
DOI :
10.1109/ICTAI.2015.31
Filename :
7372127
Link To Document :
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