Modeling the evolution of topics with time is of great value in automatic summarization and analysis of large document collections. In this work, we propose a new probabilistic gr...
Ramesh Nallapati, Susan Ditmore, John D. Lafferty,...
Machine learning approaches to coreference resolution are typically supervised, and require expensive labeled data. Some unsupervised approaches have been proposed (e.g., Haghighi...
This article contributes a generic model of topic models. To define the problem space, general characteristics for this class of models are derived, which give rise to a represent...
Although fully generative models have been successfully used to model the contents of text documents, they are often awkward to apply to combinations of text data and document met...