Papers by Stefano Melacci
Enhancing Modern Supervised Word Sense Disambiguation Models by Semantic Lexical Resources (L18-1)
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| Challenge: | Existing supervised models for Word Sense Disambiguation (WSD) are limited to knowledge-based approaches. |
| Approach: | They propose to use WordNet and WordNet Domains to enhance supervised WSD models by introducing semantic features into the classifiers and using the SLR structure to augment training data. |
| Outcome: | The proposed model improves the state-of-the-art in Word Sense Disambiguation (WSD) The proposed approach is compared with the state of the art in the most popular benchmarks. |