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 ...
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. In the current literature, the properties of algorithms to mine ass...
In this paper, we propose a probabilistic method to model the dynamic traffic flow across nonoverlapping camera views. By assuming the transition time of object movement follows a...
Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...
This paper presents an interdisciplinary investigation of statistical information retrieval (IR) techniques for protein identification from tandem mass spectra, a challenging probl...