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A Contextual Dynamic Network Model for WSD Using Associative Concept Dictionary

Many of the Japanese ideographs (Chinese characters) have a few meanings. Such ambiguities should be identified by using their contextual information. For example, we have an ideograph which has two pronunciations, /hitai/ and /gaku/, the former means a forehead of the human body and the latter has two meanings, an amount of money and a picture frame. Conventional methods for such a disambiguation problem have been using statistical methods with co-occurrence of words in their context. In this research, Contextual Dynamic Network Model is developed using the Associative Concept Dictionary which includes semantic relations among concepts/words and the relations can be represented with quantitative distances. In this model, an interactive activation method is used to identify a word’s meaning on the Contextual Semantic Network where the activation on the network is calculated using the distances. The proposed method constructs dynamically the Contextual Semantic Network according to the input words sequentially that appear in the sentence including an ambiguous word.