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- W1843634162 abstract "This paper addresses the problem of constructing a semantic hierarchy for a machine translation system. We propose two methods of constructing a hierarchy: acquiring a hierarchy from scratch and updating a hierarchy. When acquiring a hierarchy from scratch, translation rules are learned by an inductive learning algorithm in the first step. A new hierarchy is then generated by applying a clustering method to internal disjunctions of the learned rules and new rules are learned under the bias of this hierarchy. When updating an existing manually-constructed hierarchy, we take advantage of its node structure. We report experimental results showing that the semantic hierarchies generated by our method yield learned translation rules with higher average accuracy." @default.
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- W1843634162 date "1996-01-01" @default.
- W1843634162 modified "2023-09-26" @default.
- W1843634162 title "Acquiring and updating hierarchical knowledge for machine translation based on a clustering technique" @default.
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- W1843634162 doi "https://doi.org/10.1007/3-540-60925-3_57" @default.
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