3次元自己組織化メモリの提案と自然言語からの知識抽出への応用

Transactions of the Japanese Society for Artificial Intelligence 21:73-80 (2006)
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Abstract

In this paper, we propose a 3-dimensional self-organizing memory and describe its application to knowledge extraction from natural language. First, the proposed system extracts a relation between words by JUMAN and KNP, and stores it in short-term memory. In the short-term memory, the relations are attenuated with the passage of processing. However, the relations with high frequency of appearance are stored in the long-term memory without attenuation. The relations in the long-term memory are placed to the proposed 3-dimensional self-organizing memory. We used a new learning algorithm called ``Potential Firing'' in the learning phase. In the recall phase, the proposed system recalls relational knowledge from the learned knowledge based on the input sentence. We used a new recall algorithm called ``Waterfall Recall'' in the recall phase. We added a function to respond to questions in natural language with ``yes/no'' in order to confirm the validity of proposed system by evaluating the quantity of correct answers.

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