The degree of association between concepts using the chain of concepts

It is thought that the main elements of commonsense judgment similar to human beings are the concept-base and the association mechanism based on the association between concepts. It is expected that the structure of the concept-base should be as simple as possible since the concept-base has to be expanded and refined by automated learning. The 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. With experimental results using the concept-base which consists of about 40000 concepts, it is shown that the proposed method outputs a closer degree of association to that decided by human judgment than the conventional method.