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首页> 外文会议>International Florida Artificial Intelligence Research Society Conference(FLAIRS 2004) vol.2; 20040517-19; Miami Beach,FL(US) >Combining Methods for Word Sense Disambiguation of WordNet Glosses
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Combining Methods for Word Sense Disambiguation of WordNet Glosses

机译：WordNet Gloss词义消歧的组合方法

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摘要

This paper presents a new approach for combining different semantic disambiguation methods that are part of a Word Sense Disambiguation(WSD) system. The way these methods are combined greatly influences the overall system performance. The approach is based on generating training examples, for each sense of the word, based on the output of each disambiguation method. A set of rules is learned from the training examples and then applied to optimize the output of the WSD system. We tested this approach on disambiguat-ing WordNet glosses. However the approach is applicable to any WSD system. Our approach yielded a 3% gain in performance when compared with more traditional approaches such as selecting the sense given by the best disambiguation method or summing up the contribution of each method.
机译：本文提出了一种新方法，用于组合作为词义消歧（WSD）系统一部分的不同语义消歧方法。这些方法的组合方式极大地影响了整个系统的性能。该方法基于每种消歧方法的输出，针对单词的每种含义生成训练示例。从训练示例中学习了一组规则，然后将其应用于优化WSD系统的输出。我们在区分WordNet词汇上测试了这种方法。但是，该方法适用于任何WSD系统。与更传统的方法（例如，选择最佳消歧方法所赋予的意义或总结每种方法的贡献）相比，我们的方法在性能上提高了3％。

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