Adaptive System Behavior through Dynamic Data Modeling and Auto-Generated User Interface

Chameleon represents a synthesis of standards, frameworks, tools and processes that achieves adaptive system behavior. It does so by keeping a log of user interactions and utilizing an analytics engine to perform state-trace-analysis and probabilistic computations on that information, with the goal of learning a user’s preferences. The preferences themselves are in the context of the application domain model, which results in the ability to feed the results of the analytic computations back in near-real-time to the application rendering engine. The result is a UI that is built on-the-fly and adapts to the user’s usage over time. The application domain model is built in terms of a higher level metamodel that allows for a dynamic data store that can evolve over time without requiring schema changes. The result is a dynamic data model, and a system that requires no downtime when SMEs and data modelers make necessary modifications to the application domain. Agents crawl data sources, analyze and align ontologies, then link to and translate data. The architecture itself is adaptable. The analytics engine and preferences module both utilize plug-in architectures because research in adaptive systems is ongoing and new strategies for solving the problems of adaptive systems are inevitable.