Data Mining and Knowledge Management

At the heart of every intelligent system is a set of rules that allow it to respond to events in a dynamic environment. The Data and Knowledge management area of this research strength focuses on the formation, storage, and processing of these rules, and how information flows can be managed to make intelligent systems function more efficiently and effectively. The core interests in this area of research are multi-criteria decision making, which requires considering a large number of complex factors as multiple evaluation criteria; strategy, standards and frameworks for developing domain ontologies and metadata; and the disambiguation, integration and reuse of data across various applications. This core is extended in two directions: modeling the human interface at the level of what people expect of intelligent systems in terms of signals and reactions to support the development of intelligent robotics and autonomous software agents, and knowledge discovery in databases based on adaptive algorithms to enhance intelligent decision support systems.