Learning Semantically and Additively Compositional Distributional Representations
This paper connects a vector based composition model to a formal semantics, the Dependency based Compositional Semantics (DCS) We show theoretical evidence that the vector compositions in our model conform to the logic of DCS. Experimentally, we show that vector based composition brings a strong ability to calculate similar phrases as similar vectors, achieving near state of the art on a wide range of phrase similarity tasks and relation classification; meanwhile, DCS can guide building vectors for structured queries that can be directly executed. We evaluate this utility on sentence completion task and report a new state of the art.
ACL