Derivational Smoothing for Syntactic Distributional Semantics
Sebastian Padó, Jan Šnajder, Britta D. Zeller · Meeting of the Association for Computational Linguistics · 2013
Syntax-based vector spaces are used widely in lexical semantics and are more versatile than word-based spaces (Baroni and Lenci, 2010). However, they are also sparse, with resulting reliability and coverage problems. We address this problem by derivational smoothing, which uses knowledge about derivationally related words (oldish! old) to improve semantic similarity estimates. We develop a set of derivational smoothing methods and evaluate them on two lexical semantics tasks in German. Even for models built from very large corpora, simple derivational smoothing can improve coverage considerably.