Authors:
Wiem Khlif
1
and
Hanêne Ben-abdallah
2
Affiliations:
1
University of Sfax, Tunisia
;
2
King Abdulaziz University and University of Sfax, Saudi Arabia
Keyword(s):
BPM, Knowledge Discovery, Knowledge Rediscovery, Affiliation, Restructuring, Social Network Model, Hierarchical Clustering.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Process Management
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
Current trends in organization restructuring focus on the social relationships among the organizational
actors in order to improve the business process. Proposed business process model restructuring approaches
adopt either social network discovery or rediscovery techniques. Social network discovery uses semantic
information to guide the affiliation process during its analyses, whereas social network rediscovery uses
structural information to identify groups in the social network. In this paper, we propose a hybrid method
that exploits both knowledge discovery and rediscovery to suggest a new structure of a business process
model that is based on performers clustering. Using the context concept, the proposed method applies a
hierarchical clustering algorithm to determine the performer partitions; the algorithm uses two newly
defined distances that account for the semantic and structural information. The method is illustrated and
evaluated experimentally to analyze its performance.