The Explanatory Power of Symbolic Similarity in Case-Based Reasoning
作者： Enric Plaza , Eva Armengol , Santiago Ontañón
DOI: 10.1007/S10462-005-4608-6
关键词: Focus (linguistics) 、 Case-based reasoning 、 Reuse 、 Computer science 、 Symbolic data analysis 、 Lazy learning 、 Domain knowledge 、 Similarity (psychology) 、 Explanatory power 、 Artificial intelligence
摘要: A desired capability of automatic problem solvers is that they can explain the results. Such explanations should justify solution proposed by solver arises from known domain knowledge. In this paper we discuss how be used in case-based reasoning (CBR) order to results classification tasks and also for solving new problems. We particularly focus on derived building a symbolic description similar aspects among cases. Moreover, show descriptions similarity exploited different processes CBR, namely retrieve, reuse, revise, retain.
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