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• W108980932 abstract "There are many places (e.g. hospital emergency rooms) where reliable diagnostic systems might support people in their work. They could have form of RBSs with uncertainty and use the techniques of forward and backward chaining in their reasoning. The number and the contents of derived hypotheses depend then both on the form of the system’s knowledge base and on the inference engine performance. The paper provides detailed considerations on designing and applying particular uncertain rules, namely 2-uncertain rules. They are equipped with two reliability factors, representing a kind of second order probability. The rules can be acquired from real data of attributive representation. In the paper we propose a method for calculating the two reliability factors. We also suggest how to take advantage of the factors during reasoning, in order to obtain reliable hypotheses. The factors help to rank the rules and to fire them in the best order." @default.
• W108980932 created "2016-06-24" @default.
• W108980932 creator A5003028459 @default.
• W108980932 creator A5011210127 @default.
• W108980932 date "2013-01-01" @default.
• W108980932 modified "2023-09-27" @default.
• W108980932 title "Machine Ranking of 2-Uncertain Rules Acquired from Real Data" @default.
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• W108980932 doi "https://doi.org/10.1007/978-3-642-41776-4_9" @default.
• W108980932 hasPublicationYear "2013" @default.
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