We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
We present an approach to combining three areas of research which we claim are all based on information theory: knowledge representation in Artificial Intelligence and Cognitive Sc...
A novel random text generation model is introduced. Unlike in previous random text models, that mainly aim at producing a Zipfian distribution of word frequencies, our model also ...
Abstract. We study the complexity of model expansion (MX), which is the problem of expanding a given finite structure with additional relations to produce a finite model of a giv...
Antonina Kolokolova, Yongmei Liu, David G. Mitchel...
We propose to enhance a schema integration process with a validation phase employing logic-based data models. In our methodology, we validate the source schemas against the data mo...