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Symbolic connectionism in natural language disambiguation
1998
IEEE Transactions on Neural Networks
Natural language understanding involves the simultaneous consideration of a large number of different sources of information. Traditional methods employed in language analysis have focused on developing powerful formalisms to represent syntactic or semantic structures along with rules for transforming language into these formalisms. However, they make use of only small subsets of knowledge. This article will describe how to use the whole range of information through a neurosymbolic architecture
doi:10.1109/72.712149
pmid:18255763
fatcat:jwqgdg3gcjatjiby7yezvuwfh4