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.
|ホスト出版物のタイトル||Proceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012|
|出版ステータス||Published - 2012|
|イベント||6th IEEE International Conference on Semantic Computing, ICSC 2012 - Palermo|
継続期間: 2012 9 19 → 2012 9 21
|Other||6th IEEE International Conference on Semantic Computing, ICSC 2012|
|Period||12/9/19 → 12/9/21|
ASJC Scopus subject areas