Abstract
Feature sparseness is one of the main causes for Word Sense Disambiguation (WSD) systems to fail, as it increases the probability of incorrect predictions. In this work, we present a WSD method to overcome this problem by using an automatically-created thesaurus to append related words to a specific context, in order to improve the effectiveness of candidate selection for an ambiguous word. We treat the context as a vector of words taken from sentences, and expand it with words from the thesaurus according to their mutual relatedness. Our results suggest that the method performs disambiguation with high precision.
Original language | English |
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Title of host publication | Proceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012 |
Pages | 339-341 |
Number of pages | 3 |
DOIs | |
Publication status | Published - 2012 |
Externally published | Yes |
Event | 6th IEEE International Conference on Semantic Computing, ICSC 2012 - Palermo Duration: 2012 Sep 19 → 2012 Sep 21 |
Other
Other | 6th IEEE International Conference on Semantic Computing, ICSC 2012 |
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City | Palermo |
Period | 12/9/19 → 12/9/21 |
ASJC Scopus subject areas
- Software