An Analogy reasoning model for Semantic Link Network
作者： Junsheng Zhang , Yunchuan Sun
DOI: 10.4156/JDCTA.VOL4.ISSUE7.12
关键词:
摘要: Analogy reasoning is one of the most important means human thinking. How to implement analogy automatically with computers has been a hot topic in artificial intelligence and psychology. This paper proposes mathematic model for over semantic link network (SLN). We propose reliable theorem SLN based on category theory some algorithms have developed analogical by constructing functor between SLNs. Meanwhile, we also discuss conjecture models which may be unreliable but useful giving suggestions solving given problem. A study cases proposed show validity efficiency algorithms.
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