In this paper the problem of long and not quite efficient inference process is considered. There is some problem with large set of data, e.g. set of rules, which causes long time of inference process. The paper present the idea of hierarchical structure of knowledge base, where on each level of hierarchy there are created some groups of similar rules. The cluster analysis method has been used to build clusters of rules. Then, the interpreter of rules want be searching set of rules step by step (one by one). It has to be founded the most similar group of rules and all inference processes working on this small (exact) set of rules. © 2006 Springer.
CITATION STYLE
Nowak, A., & Wakulicz-Deja, A. (2006). The inference processes on clustered rules. In Advances in Soft Computing (Vol. 35, pp. 403–411). https://doi.org/10.1007/3-540-33521-8_44
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