Fusion of Multiple Semantic Networks and Human Association

We are trying to construct a conceptual system that accurately represents human thoughts by fusing of semantic networks. As semantic networks to fuse, we use the Japanese Wordnet which is a thesaurus made manually based on linguistic intuition and the knowledge acquired automatically from the actual text stored in the huge corpus. Such knowledge are represented as mutual relations of the concepts of words. In order to acquire such relations, we focus on the case relations in sentences and calculate inclusive relations of co-occurrence by using Complementary Similarity Measure. As an application and verification of the conceptual system created, we try to simulate human associations by using the conceptual system. As an experimental result, we found the obvious difference in generated association links between using the semantic network of Japanese Wordnet and using the fused semantic networks with Japanese Wordnet and the acquired mutual relations.