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...
Multinomial distributions over words are frequently used to model topics in text collections. A common, major challenge in applying all such topic models to any text mining proble...
This paper presents a statistical model for discovering topical clusters of words in unstructured text. The model uses a hierarchical Bayesian structure and it is also able to iden...
We describe a joint probabilistic model for modeling the contents and inter-connectivity of document collections such as sets of web pages or research paper archives. The model is...
Background: Microarray studies provide a way of linking variations of phenotypes with their genetic causations. Constructing predictive models using high dimensional microarray me...