Paper: Gloss-Based Semantic Similarity Metrics for Predominant Sense Acquisition

ACL ID I08-1073
Title Gloss-Based Semantic Similarity Metrics for Predominant Sense Acquisition
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2008
Authors

In recent years there have been various ap- proaches aimed at automatic acquisition of predominant senses of words. This infor- mation can be exploited as a powerful back- off strategy for word sense disambiguation given the zipfian distribution of word senses. Approaches which do not require manually sense-tagged data have been proposed for English exploiting lexical resources avail- able, notably WordNet. In these approaches distributional similarity is coupled with a se- manticsimilaritymeasurewhichtiesthedis- tributionally related words to the sense in- ventory. The semantic similarity measures that have been used have all taken advantage of the hierarchical information in WordNet. We investigate the applicability to Japanese and demonstrate the feasibility of a mea- sure which uses o...