We propose a novel bilingual topical admixture (BiTAM) formalism for word alignment in statistical machine translation. Under this formalism, the parallel sentence-pairs within a ...
Traditional models of information retrieval assume documents are independently relevant. But when the goal is retrieving diverse or novel information about a topic, retrieval mode...
Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
In this paper, we develop the continuous time dynamic topic model (cDTM). The cDTM is a dynamic topic model that uses Brownian motion to model the latent topics through a sequenti...
We propose a latent variable model to enhance historical analysis of large corpora. This work extends prior work in topic modelling by incorporating metadata, and the interactions...
William Yang Wang, Elijah Mayfield, Suresh Naidu, ...