Authors:
Nilander R. M. de Moraes
;
Luis E. Zárate
and
Henrique C. Freitas
Affiliation:
Pontifical Catholic University of Minas Gerais, Brazil
Keyword(s):
Formal concept analysis, FCA, Information retrieval.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Sensor Networks
;
Signal Processing
;
Society, e-Business and e-Government
;
Soft Computing
;
Software Engineering
;
Web Information Systems and Technologies
Abstract:
The processing of dense contexts is a common problem in Formal Concept Analysis. From input contexts, all possible combinations must be evaluated in order to obtain all correlations between objects and attributes. The state-of-the-art shows that this problem can be solved through distributed processing. Partial concepts would be obtained from a distributed environment composed of machine clusters in order to achieve the final set of concepts. Therefore, the goal of this paper is to propose, develop, and evaluate a distributed algorithm with high performance to solve the problem of dense contexts. The speedup achieved through the distributed algorithm shows an improvement of performance, but mainly, a high-balance workload which reduces the processing time considerably. For this reason, the main contribution of this paper is the distributed algorithm, capable of accelerating the processing for dense formal contexts.