The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
Named Entity Recognition and Classification is being studied for last two decades. Since semantic features take huge amount of training time and are slow in inference, the existing...
Siddhartha Jonnalagadda, Robert Leaman, Trevor Coh...
Abstract. One of the most appealing features of constraint programming is its rich constraint language for expressing combinatorial optimization problems. This paper demonstrates t...
This paper describes, and evaluates benefits of, a design methodology to translate certain mathematical models into the design of novel, self-adaptive, peer-to-peer (p2p) distrib...
Abstract. Web applications represent an important category of applications that owe much of their popularity to the ubiquitous accessibility using standard web browsers. The comple...