Public health-related topics are difficult to identify in large conversational datasets like Twitter. This study examines how to model and discover public health topics and themes ...
Kyle W. Prier, Matthew S. Smith, Christophe G. Gir...
Previously topic models such as PLSI (Probabilistic Latent Semantic Indexing) and LDA (Latent Dirichlet Allocation) were developed for modeling the contents of plain texts. Recent...
Abstract--Statistical approaches to document content modeling typically focus either on broad topics or on discourselevel subtopics of a text. We present an analysis of the perform...
Leonhard Hennig, Thomas Strecker, Sascha Narr, Ern...
Modeling text with topics is currently a popular research area in both Machine Learning and Information Retrieval (IR). Most of this research has focused on automatic methods thou...
Probabilistic latent topic models have recently enjoyed much success in extracting and analyzing latent topics in text in an unsupervised way. One common deficiency of existing to...