Abstract
Most word sense disambiguation (WSD) methods require large quantities of manually annotated training data and/or do not exploit fully the semantic relations of thesauri. We propose a new unsupervised WSD algorithm, which is based on generating Spreading Activation Networks (SANs) from the senses of a thesaurus and the relations between them. A new method of assigning weights to the networks' links is also proposed. Experiments show that the algorithm outperforms previous unsupervised approaches to WSD.
| Original language | English |
|---|---|
| Pages (from-to) | 1725-1730 |
| Number of pages | 6 |
| Journal | IJCAI International Joint Conference on Artificial Intelligence |
| State | Published - 2007 |
| Externally published | Yes |
| Event | 20th International Joint Conference on Artificial Intelligence, IJCAI 2007 - Hyderabad, India Duration: Jan 6 2007 → Jan 12 2007 |