This paper proposes a novel framework for automatic text categorization problem based on the kernel density classifier. The overall goal is to tackle two main issues in automatic ...
Dwi Sianto Mansjur, Ted S. Wada, Biing-Hwang Juang
In this paper, we propose a topic detection method using a dialogue history for selecting a scene in the automatic interpretation system (Ikeda et al., 2002). The method uses a k-...
Topic tracking is complicated when the stories in the stream occur in multiple languages. Typically, researchers have trained only English topic models because the training storie...
Leah S. Larkey, Fangfang Feng, Margaret E. Connell...
We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...
How can the development of ideas in a scientific field be studied over time? We apply unsupervised topic modeling to the ACL Anthology to analyze historical trends in the field of...
David Hall, Daniel Jurafsky, Christopher D. Mannin...