5. Conclusions and Future Study Directions
In the era of knowledge economy, information and knowledge has become an important resource. Knowledge
discovered from data mining can support SMBs to improve decision-making level by our knowledge cultivating
method. The method integrates Extenics, data mining and knowledge management, and can develop a decision
support system platform. By collecting knowledge or information from conditions and the goal among all
departments in SBMs, this platform can share knowledge from every employee in varies forms. Knowledge or
information related to the conditions or goals of the problem can find relations by human-computer interaction
method. Divergence analysis, correlation analysis and implication analysis have been used in the platform and
proved useful to extend knowledge reference range. Then it forms the knowledge tree, in which the problem-solving
map can guide the managers to take actions by scanning all possible paths. A simple intelligent knowledge
management platform can support decision-making process efficently in SMBs.
But the algorithm we used in the paper is relatively simple, the knowledge mapping process need to be improved
more intelligent so as to remind what kind of information should be supplied. On the other hand, knowledge and
information can even reasoning and produce new knowledge. How to update ontology automatically and simulate
the knowledge cultivating process by intelligent agent is the next research work. Moreover, Fuzzy set, complexity
Science and social agent technology will be utilized to improve the platform.