Learning Lexical Subspaces in a Distributional Vector Space
In this paper, we propose LexSub, a novel approach towards unifying lexical and distributional semantics.We inject knowledge about lexical-semantic relations into distributional word embeddings by defining subspaces of the distributional vector space in koip share price which a lexical relation should hold.Our framework can handle symmetric attract