Ambiguity is a problem we frequently face in Natural Language Processing. Word Sense Disambiguation (WSD) is a task to determine the correct sense of an ambiguous word. However, research in WSD for Indonesian is still rare to find. The availability of English-Indonesian parallel corpora and WordNet for both languages can be used as training data for WSD by applying Cross-Lingual WSD method. This training data is used as an input to build a model using supervised machine learning algorithms. Our research also examines the use of Word Embedding features to build the WSD model.
|Publication status||Published - 1 Jan 2018|
|Event||9th Global WordNet Conference, GWC 2018 - Singapore, Singapore|
Duration: 8 Jan 2018 → 12 Jan 2018
|Conference||9th Global WordNet Conference, GWC 2018|
|Period||8/01/18 → 12/01/18|