In this paper, we explored how to use meta-data information in information retrieval task. We presented a new language model that is able to take advantage of the category informa...
Rong Jin, Luo Si, Alexander G. Hauptmann, James P....
Probabilistic models of languages are fundamental to understand and learn the profile of the subjacent code in order to estimate its entropy, enabling the verification and predicti...
We develop a general method to match unstructured text reviews to a structured list of objects. For this, we propose a language model for generating reviews that incorporates a de...
Nilesh N. Dalvi, Ravi Kumar, Bo Pang, Andrew Tomki...
In this paper, with a belief that a language model that embraces a larger context provides better prediction ability, we present two extensions to standard n-gram language models ...
In this paper, we propose a new Bayesian model for fully unsupervised word segmentation and an efficient blocked Gibbs sampler combined with dynamic programming for inference. Our...