Use semantic decision tables to improve meaning evolution support systems

Abstract

Meaning Evolution Support Systems have been recently introduced as a real-time, scalable, community-based cooperative systems to support the ontology evolution. In this paper, we intend to address the problems of accuracy and effectiveness in Meaning Evolution Support Systems in general. We use Semantic Decision Tables to tackle these problems. A Semantic Decision Table separates general decision rules from the processes, bootstraps policies and template dependencies in the whole system. Recently, DOGMA-MESS ("Developing Ontology Grounded Methodology and Applications" framework based "Meaning Evolution Support Systems") is developed at VUB STARLab as a collection of meaning evolution support systems. We embed Semantic Decision Tables in DOGMA-MESS to illustrate our approach. Semantic Decision Tables play the roles in both top-down and bottom-up processes of the meaning evolution cycle. The decision rules that consist of templates dependency rules are mainly responsible for the top-down process execution. The bottom-up process execution relies on the ones that contain the concept lifting algorithms. © 2008 Springer-Verlag Berlin Heidelberg.