Reactive business intelligence
Reactive business intelligence (RBI) advocates an holistic approach that integrates data mining, modeling and interactive visualization, into an end-to-end discovery and continuous innovation process powered by human and automated learning.
Relationships with reactive search optimization (RSO)
RSO is a multi-disciplinary research area between operations research (optimization), computer science, machine learning and neural networks that studies online learning schemes applied to problem-solving and optimization, according to a learning while optimizing principle . The word reactive hints at a ready response to events during the search through an internal feedback loop for online self-tuning and dynamic adaptation. Online adaptation and model revision is used in reactive business intelligence to adapt the data mining and interactive visualization techniques to the knowledge derived from a user in real time.
- Roberto Battiti and Mauro Brunato, Reactive Business Intelligence. From Data to Models to Insight, Reactive Search Srl, Italy, February 2011. ISBN 978-88-905795-0-9.
- Battiti, Roberto; Andrea Passerini (2010). "Brain-Computer Evolutionary Multi-Objective Optimization (BC-EMO): a genetic algorithm adapting to the decision maker." (PDF). IEEE Transactions on Evolutionary Computation 14 (15): 671–687. doi:10.1109/TEVC.2010.2058118
- Battiti, Roberto; Mauro Brunato; Franco Mascia (2008). Reactive Search and Intelligent Optimization. Springer Verlag. ISBN 978-0-387-09623-0.