We describe an architecture for representing and managing context shifts that supports dynamic data interpretation. This architecture utilizes two layers of learning and three lay...
Nikita A. Sakhanenko, George F. Luger, Carl R. Ste...
Language comprehension in humans is significantly constrained by memory, yet rapid, highly incremental, and capable of utilizing a wide range of contextual information to resolve ...
Roger P. Levy, Florencia Reali, Thomas L. Griffith...
We examine the possible use of Description Logics as a knowledge representation and reasoning system for high-level scene interpretation. It is shown that aggregates composed of m...
This work introduces a formal framework for the social acquisition of ontologies which are constructed dynamically from overhearing the possibly conflicting symbolic interaction o...
We propose a novel context sensitive algorithm for evaluation of ordinal attributes which exploits the information hidden in ordering of attributes’ and class’ values and prov...