{"type":"ScholarlyArticle","title":"Optimizing Classifier Performance in Word Sense Disambiguation by Redefining Sense Classes","authors":[{"name":"Upali Sathyajith Kohomban","slug":"upali-sathyajith-kohomban","given":"Upali Sathyajith","family":"Kohomban","affiliation":""},{"name":"Wee Sun Lee","slug":"wee-sun-lee","given":"Wee Sun","family":"Lee","affiliation":""}],"abstract":"Learning word sense classes has been shown to be useful in fine-grained word sense disambiguation. However, the common choice for sense classes, WordNet lexicographer files, are not designed for machine learning based word sense disambiguation. In this work, we explore the use of clustering techniques in an effort to construct sense classes that are more suitable for word sense disambiguation end-task. Our results show that these classes can significantly improve classifier performance over the state of the art results of unrestricted word sense disambiguation.","doi":null,"url":"https://ijcai.org/proceedings/2007/264","pdf":"https://ijcai.org/proceedings/2007/0264.pdf","markdown":"https://ijcai.org/proceedings/2007/264.md","bibtex":"https://ijcai.org/proceedings/2007/bibtex/264","volume":{"slug":"2007","title":"Proceedings of the Twentieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2007","url":"https://ijcai.org/proceedings/2007/","year":2007,"location":"Hyderabad, India","dates":"","editors":"Ramon López de Mántaras","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":264,"pages":{"first":1635,"last":1639},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}