Paper: Towards Syntax-aware Compositional Distributional Semantic Models

ACL ID C14-1068
Title Towards Syntax-aware Compositional Distributional Semantic Models
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014

Compositional Distributional Semantics Models (CDSMs) are traditionally seen as an entire dif- ferent world with respect to Tree Kernels (TKs). In this paper, we show that under a suitable regime these two approaches can be regarded as the same and, thus, structural information and distributional semantics can successfully cooperate in CSDMs for NLP tasks. Leveraging on distributed trees, we present a novel class of CDSMs that encode both structure and distribu- tional meaning: the distributed smoothed trees (DSTs). By using DSTs to compute the similarity among sentences, we implicitly define the distributed smoothed tree kernels (DSTKs). Exper- iment with our DSTs show that DSTKs approximate the corresponding smoothed tree kernels (STKs). Thus, DSTs encode both structural and distribution...