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A stochastic model for Case-Based Reasoning

机译:基于案例推理的随机模型

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摘要

Case-Based Reasoning (CBR) is the process of solving new problems based on the solution of similar past problems. In the present paper we introduce an absorbing Markov chain on the main steps of the CBR process. In this way we succeed in obtaining the probabilities for the above process to be in a certain step at a certain phase of the solution of the corresponding problem, and a measure for the efficiency of a CBR system. Examples are also given to illustrate our results.
机译:基于案例的推理(CBR)是基于解决过去类似问题而解决新问题的过程。在本文中,我们在CBR工艺的主要步骤上引入了吸收性马尔可夫链。这样,我们成功地获得了上述过程在相应问题的解决方案的某个阶段处于某个步骤中的概率,以及CBR系统效率的度量。实例还说明了我们的结果。

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