Paper Info
Title
Modeling and Analyzing Process Architecture for Context-Driven Adaptation: Designing Cognitively-Enhanced Business Processes for Enterprises
Abstract
Organizations are increasingly looking to adopt and incorporate cognitive capabilities into key business processes to aid human decision-making activities. The availability of context data helps with improved decision-making involving both human users and cognitive systems, while ensuring continuing satisfaction of enterprise objectives. Therefore, the ongoing monitoring, selection and management of context data for redesigning sections of the overall business process structure, particularly where the cognitive systems are integrated in business processes, is of great interest. This paper proposes a systematic model-based approach to visualize the detection of context changes in a business process, determine an appropriate response to this context change, and identify the corresponding reconfiguration of processes in another part of the enterprise. This paper not only handles context, but also looks at the processes that need to respond to changes in that context. Together these processes constitute a business process architecture. This enables business process reconfiguration to better integrate cognitive systems in process activities requiring decision-making. The use of such modeling techniques facilitates the investigation of multiple process configurations while considering satisfaction of functional and non-functional objectives and ongoing contextual changes.
Year
DOI
Venue
2018
10.1109/EDOC.2018.00018
2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)
Keywords
Field
DocType
Cognitive Computing, Enterprise Modeling, Conceptual Modeling, Business Process Management
Business process management,Business process,Conceptual model,Systems engineering,Work in process,Computer science,Enterprise modelling,Process architecture,Cognitive computing,Business architecture,Process management
Conference
ISSN
ISBN
Citations 
2325-6354
978-1-5386-4140-8
0
PageRank 
References 
Authors
0.34
15
5
Name
Order
Citations
PageRank
Zia Babar172.25
Alexei Lapouchnian257531.57
Eric S. K. Yu3172.17
Allen Chan4364.60
Sebastian Carbajales500.68