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概要
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It is thought that the main elements of commonsense judgement similar to human beings are a concept-base and the association mechanism based on the association between concepts. It is expected that the structure of the concept-base be as simple as possible since the concept-base has to be expanded and refined automatically by automated learning. This paper proposes a new method of measuring the degree of association between concepts. In the conventional method, a concept is expressed by first attributes vector model, and the degree of association between concepts is derived from an inner product of vectors. In this model, since each first attribute must be converted to its category, a category database such as a thesaurus is required. By the proposed method, the degree of association is derived using the chain of concepts without category. By experimental results using the concept-base, which consists of about 40, 000 concepts, it is shown that the proposed method outputs the closer degree of association to that decided by human judgement than the conventional method.
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