Abstract
The authors propose to use cluster analysis techniques (particularly clustering) to speed-up the process of finding rules to be activated in complex decision support systems with incomplete knowledge. The authors also wish to inference within such decision support systems using rules, of which premises are not fully covered by the facts. The AHC or mAHC algorithm is used. The authors adapted Salton’s most promising path method with own modifications for a fast look-up of the rules.
Keywords
- knowledge bases
- cluster analysis
- clustering
- decision support systems
- incomplete knowledge
- inference
- AHC
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Nowak-Brzezińska, A., Jach, T., Wakulicz-Deja, A. (2012). Inference Processes Using Incomplete Knowledge in Decision Support Systems – Chosen Aspects. In: Yao, J., et al. Rough Sets and Current Trends in Computing. RSCTC 2012. Lecture Notes in Computer Science(), vol 7413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32115-3_17
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DOI: https://doi.org/10.1007/978-3-642-32115-3_17
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