Paper: A Tensor-based Factorization Model of Semantic Compositionality

ACL ID N13-1134
Title A Tensor-based Factorization Model of Semantic Compositionality
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

In this paper, we present a novel method for the computation of compositionality within a distri- butional framework. The key idea is that com- positionality is modeled as a multi-way interac- tion between latent factors, which are automat- ically constructed from corpus data. We use our method to model the composition of sub- ject verb object triples. The method consists of two steps. First, we compute a latent factor model for nouns from standard co-occurrence data. Next, the latent factors are used to induce a latent model of three-way subject verb object interactions. Our model has been evaluated on a similarity task for transitive phrases, in which it exceeds the state of the art.