Unsupervised and Constrained Dirichlet Process Mixture Models for Verb 

Speaker: Andreas Vlachos Computer Laboratory Cambridge 

University Abstract:  

In this work we apply Dirichlet Process Mixture Models (DPMMs) to a learning task in natural language processing (NLP): lexical-semantic verb clustering. Furthermore, we propose a novel method of guiding the DPMM towards a particular clustering solution using pairwise constraints. The quantitative and qualitative evaluation performed highlights the benefits of both standard and constrained DPMMs compared to previously used approaches