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Fusion of Multiple Semantic Networks and Human Association

机译:多种语义网络与人类协会的融合

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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.
机译:我们正在尝试构建一个通过融合语义网络来准确表示人类思想的概念系统。作为融合的语义网络,我们使用日语单词网,它是基于语言直觉和从存储在庞大语料库中的实际文本中自动获取的知识手动创建的同义词库。这种知识被表示为词语概念的相互关系。为了获得这种关系,我们关注句子中的大小写关系,并使用互补相似性度量来计算共现的包含关系。作为对创建的概念系统的应用和验证,我们尝试通过使用概念系统来模拟人类联想。作为实验结果,我们发现在使用日语Wordnet的语义网络和使用日语Wordnet的融合语义网络与获取的相互关系之间,生成的关联链接存在明显差异。

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