Paper Info
Title
Managing and Simplifying Cognitive Business Operations Using Process Architecture Models.
Abstract
Enterprises increasingly rely on cognitive capabilities to enhance their core business processes by adopting systems that utilize machine learning and deep learning approaches to support cognitive decisions to aid humans responsible for business process execution. Unlike conventional information systems, for which the design and implementation is a much-studied area, the design of cognitive systems and their integration into existing enterprise business processes is less well understood. This results in long drawn-out implementation and adoption cycles, and requires individuals with highly specialized skills. As cognitively-assisted business processes involve human and machine collaboration, non-functional requirements, such as reusability and configurability that are prominent for software system design, must also be addressed at the enterprise level. Supporting processes may emerge and evolve over time to monitor, evaluate, adjust, or modify these cognitively-enhanced business processes. In this paper, we utilize a goal-oriented approach to analyze the requirements for designing cognitive systems for simplified adoption in enterprises, which are then used to guide and inform the design of a process architecture for cognitive business operations.
Year
DOI
Venue
2019
10.1007/978-3-030-21290-2_40
ADVANCED INFORMATION SYSTEMS ENGINEERING (CAISE 2019)
Keywords
Field
DocType
Business process management,Goal modeling,Cognitive computing,Cognitive business operations,Requirements engineering
Information system,Business process management,Systems engineering,Business process,Computer science,Business operations,Requirements engineering,Process architecture,Goal modeling,Cognitive computing,Process management
Conference
Volume
ISSN
Citations 
11483
0302-9743
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Zia Babar172.25
Eric S. K. Yu21480200.75
Sebastian Carbajales321.04
Allen Chan4364.60