Learning multi-prototype word embedding from single-prototype word embedding with integrated knowledge

Xuefeng Yang, Kezhi Mao

Abstract: Highlights•A mini context word sense disambiguation with adapted Lesk algorithm is proposed•New initialization approach is proposed to balance speed and performance.•Improved approximation algorithm is proposed to help supervised learning•The framework may utilize any sense inventory with word-sense definition.