Authors:
Kaio H. A. Ananias
;
Julio C. V. Neves
;
Pedro H. B. Ruas
;
Luis E. Zárate
and
Mark A. J. Song
Affiliation:
Pontifical Catholic University of Minas Gerais (PUC Minas), R. Walter Ianni, 255 - Sao Gabriel - 31.980-110, Belo Horizonte, Minas Gerais and Brazil
Keyword(s):
Formal Concept Analisys,Triadic Concept Analisys, Binary Decision Diagram, TRIAS Algorithm.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Data Engineering
;
Data Mining
;
Databases and Data Security
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Large Scale Databases
;
Ontologies and the Semantic Web
;
Sensor Networks
;
Signal Processing
;
Society, e-Business and e-Government
;
Soft Computing
;
Web Information Systems and Technologies
Abstract:
Formal Concept Analysis (FCA) is an approach based on the mathematization and hierarchy of formal concepts. Nowadays, with the increasing of social network for personal and professional usage, more and more applications of data analysis on environments with high dimensionality (Big Data) have been discussed in the literature. Through the Formal Concept Analysis and Triadic Concept Analysis, it is possible to extract database knowledge in a hierarchical and systematized representation. It is common that the data set transforms the extraction of this knowledge into a problem of high computational cost. Therefore, this paper has an objective to evaluate the behavior of the algorithm for extraction triadic concepts using TRIAS in high dimensional contexts. It was used a synthetic generator known as SCGaz (Synthetic Context Generator a-z). After the analysis, it was proposed a representation of triadic contexts using a structure known as Binary Decision Diagram (BDD).