Case Based Reasoning as an improvement of decision making and case processing in Adaptive Case Management systems.
Łukasz Osuszek, Stanisław Stanek
DOI: http://dx.doi.org/10.15439201561
Citation: Position Papers of the 2015 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 6, pages 217–223 (2015)
Abstract. The paper sets out from a central proposition that the concept of Case Based Reasoning could improve business decisions and optimize case processing in modern Adaptive Case Management (ACM) systems. While presenting the state of the art in efforts to blend Artificial Intelligence with business process management as well as with knowledge management systems (KMS) and ACM. Authors observe that the classical ACM platform is evolving. The dynamic and adaptive nature of some business processes poses challenges that the classical BPM approach cannot adequately address. Adaptive case management has been developed to better cope with such challenges. It makes it, on the one hand, easier to align a business to rapidly changing requirements and conditions, and, on the other, it allows organizations to more effectively exploit the potential inherent in organizational knowledge and information resources. The paper discusses the evolution of ACM systems and adopting Case Based Reasoning and AI to optimize ACM outcome