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Enriching Semantic Knowledge for WSD

机译:拓展水务署的语义知识

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In our previous work, we proposed to combine ConceptNet and WordNet for Word Sense Disambiguation (WSD). The ConceptNet was automatically disambiguated through Normalized Google Distance (NGD) similarity. In this letter, we present several techniques to enhance the performance of the ConceptNet disambiguation and use this enriched semantic knowledge in WSD task. We propose to enrich both the WordNet semantic knowledge and NGD to disambiguate the concepts in ConceptNet. Furthermore, we apply the enriched semantic knowledge to improve the performance of WSD. From a number of experiments, the proposed method has been obtained enhanced results.
机译:在我们以前的工作中,我们建议将ConceptNet和WordNet结合起来进行词义消歧(WSD)。 ConceptNet通过归一化Google距离(NGD)相似度自动消除歧义。在这封信中,我们提出了几种技术来增强ConceptNet消歧的性能,并在WSD任务中使用这种丰富的语义知识。我们建议丰富WordNet语义知识和NGD,以消除ConceptNet中的概念歧义。此外,我们运用丰富的语义知识来提高WSD的性能。从大量实验中,提出的方法获得了增强的结果。

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