Abstract. Topic Maps and RDF are two independently developed paradigms and standards for the representation, interchange, and exploitation of model-based data on the web. Each para...
Topic models are a useful tool for analyzing large text collections, but have previously been applied in only monolingual, or at most bilingual, contexts. Meanwhile, massive colle...
David M. Mimno, Hanna M. Wallach, Jason Naradowsky...
Machine Learning can be divided into two schools of thought: generative model learning and discriminative model learning. While the MCS community has been focused mainly on the lat...
Topic models such as aspect model or LDA have been shown as a promising approach for text modeling. Unlike many previous models that restrict each document to a single topic, topi...
Latent Dirichlet allocation is a fully generative statistical language model that has been proven to be successful in capturing both the content and the topics of a corpus of docum...