J. Velencei (Hungary)
Knowledge sharing, Machine Learning, Knowledge Management Business Models
The DoctuS Knowledge Based System is based on the classical rule-based reasoning, topped with inductive reasoning for the situation where the expert has enough experience (cases). With the help of inductive reasoning those attributes and rules can be extracted, that give the same decision proposal as provided by the rule-based reasoning. According to our experience in business decision-making, this means that 20-25 attributes and 1500-2500 rules can be reduced to 5-9 attributes and a dozen of purified rules. The system links hard data with soft information. Hard data is "mined" from data warehouses, on the output side linked to an intelligent portal functioning on Intranet. Its benefits are rapidity and decrease in costs due to reduced number of rules, and up-to-date information thanks to the intelligent DoctuS portal.
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