We present a general framework to incorporate prior knowledge such as heuristics or linguistic features in statistical generative word alignment models. Prior knowledge plays a ro...
We present a probabilistic ranking-driven classifier for the detection of video semantic concept, such as airplane, building, etc. Most existing concept detection systems utilize ...
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
We develop a new algorithm for clustering search results. Differently from many other clustering systems that have been recently proposed as a post-processing step for Web search ...