DocumentCode :
1980913
Title :
Information and data management with links on business and swarm intelligence
Author :
Janakova, Milena
Author_Institution :
Dept. of Inf., Silesian Univ. in Opava, Karvina, Czech Republic
fYear :
2013
fDate :
23-25 Sept. 2013
Firstpage :
1
Lastpage :
6
Abstract :
This paper is centered on data and their management with links to business and swarm intelligence. Today´s information society creates large volumes of data. Firms, organizations and individuals carry out decision-making based on actual knowledge. Knowledge searching is supported by Business Intelligence products. There are standard procedures for analysis using the cube with facts and dimensions. The question is about the management of data for optimal selection within the cube. A good inspiration is brought by swarm intelligence via the Ant Colony Optimization. The cubes build environment and data attributes are used as pheromones. The designed solution is partitioned into data, cubes, links and messages. The data forms a cube environment. Links are created with searchers. They build relations between needed data via impact indicators. Messages define rules with an influence on decision-making in society. This method of auto-self cube management respects complexity in simulation of business needs as individuals via swarm intelligence.
Keywords :
ant colony optimisation; competitive intelligence; decision support systems; ant colony optimization; auto-self cube management method; business intelligence; business needs; cube environment; data management; decision making; impact indicators; information management; information society; knowledge searching; pheromones; swarm intelligence; Artificial intelligence; Bismuth; Data warehouses; Decision making; Organizations; Particle swarm optimization; Business Intelligence; cubes; data management; information; swarm intelligence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Informatics and Applications (ICIA),2013 Second International Conference on
Conference_Location :
Lodz
Print_ISBN :
978-1-4673-5255-0
Type :
conf
DOI :
10.1109/ICoIA.2013.6650240
Filename :
6650240
Link To Document :
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