Intelligent data analysis - support for development of SMEs sector

The paper studies possibilities of intelligent data analysis application for discovering knowledge hidden in small and medium-sized enterprises’ (SMEs) data, on the territory of the province of Vojvodina. The knowledge revealed by intelligent analysis, and not accessible by any other means, could be the valuable starting point for working out of proactive and preventive actions for the development of the SMEs sector.Intelligent data analysis, CRISP-DM, clustering, small and medium enterprises., Research and Development/Tech Change/Emerging Technologies, C8, L2,

Different clustering techniques : means for improved knowledge discovery

Application of different clustering techniques can result in different basic data set partitions emphasizing diversified aspects of resulting clusters. Since analysts have a great responsibility for the successful interpretation of the results obtained through some of the available tools, and for giving meaning to what forms a qualitative set of clusters, additional information attained from different tools is of a great use to them. In this article we presented the clustering results of small and medium sized enterprises’ (SMEs) data, obtained in DataEngine, iData Analyzer and Weka tools for intelligent analysis