For more than thirty years, the parallel programming community has used the dependence graph as the main abstraction for reasoning about and exploiting parallelism in “regularâ€...
Keshav Pingali, Donald Nguyen, Milind Kulkarni, Ma...
Classification of texts potentially containing a complex and specific terminology requires the use of learning methods that do not rely on extensive feature engineering. In this w...
Temporal expressions are important structures in natural language. In order to understand text, temporal expressions have to be extracted and normalized. In this paper we present a...
The ability to identify speech acts reliably is desirable in any spoken language system that interacts with humans. Minimally, such a system should be capable of distinguishing be...
We propose a novel probabilistic method based on the Hidden Markov Model (HMM) to learn the structure of a Latent Variable Model (LVM) for query language modeling. In the proposed...