This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
In this paper, we define the problem of topic-sentiment analysis on Weblogs and propose a novel probabilistic model to capture the mixture of topics and sentiments simultaneously....
Qiaozhu Mei, Xu Ling, Matthew Wondra, Hang Su, Che...
The availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. This includes methods for discover...
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kap...
In order to understand the evolution of online identities, we measured the correlation between past and current representations of self on the MySpace social network. We applied s...
—Navigating large software systems is difficult as the various artifacts are distributed in a huge space, while the relationships between different artifacts often remain hidden...