Authors:
Alfredo Cuzzocrea
1
;
Francesco Folino
2
and
Luigi Pontieri
2
Affiliations:
1
ICAR-CNR and University of Calabria, Italy
;
2
ICAR-CNR, Italy
Keyword(s):
Knowledge Representation and Management, Complex Information Systems, Process Mining.
Related
Ontology
Subjects/Areas/Topics:
Applications of Expert Systems
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Sensor Networks
;
Signal Processing
;
Society, e-Business and e-Government
;
Soft Computing
;
Web Information Systems and Technologies
Abstract:
A knowledge-based framework for supporting and analyzing loosely-structured collaborative processes (LSCPs) is presented in this paper. The framework takes advantages from a number of knowledge representation, management and processing capabilities, including recent process mining techniques. In order to support the enactment, analysis and optimization of LSCPs in an Internet-worked virtual scenario, we illustrate a flexible integration architecture, coupled with a knowledge representation and discovery environment, and enhanced by ontology-based knowledge processing capabilities. In particular, an approach for restructuring logs of LSCPs is proposed, which allows to effectively analyze LSCPs at varying abstraction levels with process mining techniques (originally devised to analyze well-specified and well-structured workflow processes). The capabilities of the proposed framework were experimentally tested on several application contexts. Interesting results that concern the experime
ntal analysis of collaborative manufacturing processes across a distributed CAD platform are shown.
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