Knowledge cultivating for intelligent decision making in small & middle businesses

Abstract

Small and middle businesses (SMBs) are playing an increasingly important role, but their decision making process mostly relies on skilled employees which are usually inadequate. Based on information systems, data mining and Extension Theory (Extenics), we present a knowledge cultivating method and design a knowledge management platform for improve decision making quality. Through divergence analysis, correlation analysis, and implication analysis, a flow chart of knowledge cultivating algorithm has been designed, and an intelligent knowledge management platform has been developed. By collecting knowledge or information from conditions and the goal, we choose several knowledge as seed, then distribute it to all the department leaders, let them input relative knowledge including data mining knowledge to the platform. The platform then connects them into a knowledge tree with Human-Computer Interaction and enterprise ontology techniques intelligently. From the knowledge tree, we can find the problem solving map and guide the managers in SBMs to take actions by scanning all possible paths. The application in a food company proved its practicality value.

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