In this work we apply Dirichlet Process Mix- ture Models to a learning task in natural language processing (NLP): lexical-semantic verb clustering. We assess the performance on a dataset based on Levin’s (1993) verb classes using the recently introduced V- measure metric. In, we present a method to add human supervision to the model in or- der to to influence the solution with respect to some prior knowledge. The quantitative evaluation performed highlights the benefits of the chosen method compared to previously used clustering approaches.
CITATION STYLE
Vlachos, A., Ghahramani, Z., & Korhonen, A. (2008). Dirichlet Process Mixture Models for Verb Clustering. Proceedings of the ICML Workshop on Prior Knowledge for Text and Language Processing, Helsinki, Finland, 1–6. Retrieved from papers3://publication/uuid/612EDB87-A804-46C9-8254-BF5351273773
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