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Modelling Decision Support Systems using Conceptual Constraints - Linking Process Systems Engineering and Decision Making Models

Topics: Applications and Case-Studies; Decision Support Systems; Domain Analysis and Modeling; Domain Ontologies; Enterprise Engineering; Enterprise Ontology; Expert Systems; Integration and Interoperability; Knowledge Engineering; Natural Language Processing; Ontology Engineering

Authors: Canan Dombayci and Antonio Espuña

Affiliation: Universitat Politècnica de Catalunya, Spain

Keyword(s): Knowledge Engineering, Ontology Engineering, Decision Support Systems, Mathematical Programming, Conceptual Constraint Domain, Process Systems Engineering.

Related Ontology Subjects/Areas/Topics: Applications ; Applications and Case-studies ; Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Domain Analysis and Modeling ; e-Business ; Enterprise Engineering ; Enterprise Information Systems ; Enterprise Ontology ; Expert Systems ; Health Engineering and Technology Applications ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Natural Language Processing ; Ontologies and the Semantic Web ; Ontology Engineering ; Pattern Recognition ; Symbolic Systems

Abstract: This paper presents the use of a Conceptual Constraint (CC) Domain to systematize the construction of Decision Making Models (DMMs). The modelling systematics include the integration between the CC Domain and production systems as well as an identification procedure which contains some steps aimed at constraint identification using the CC Domain. The CC Domain consists of different modelling elements such as Conceptual Constraints (generic constraint types), Conceptual Components (pieces of a constraint), and Conceptual Component Elements (pieces of a conceptual component that may be connected to production systems). In this instance, the CC Domain is integrated with the Process Systems Engineering (PSE) Domain as a production system domain. The PSE Domain contains information from the multi-level functional hierarchical in an enterprise and it will be used to cover a wide range of scenarios related to hierarchical integration of DMMs. In addition, an integration step between the CC and PSE Domains is illustrated. The focus of the work is to show how these models should be developed in order to be properly integrated, and how they are used by different functionalities with an identification procedure. (More)

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Paper citation in several formats:
Dombayci, C. and Espuña, A. (2017). Modelling Decision Support Systems using Conceptual Constraints - Linking Process Systems Engineering and Decision Making Models. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD; ISBN 978-989-758-272-1; ISSN 2184-3228, SciTePress, pages 147-154. DOI: 10.5220/0006485201470154

@conference{keod17,
author={Canan Dombayci. and Antonio Espuña.},
title={Modelling Decision Support Systems using Conceptual Constraints - Linking Process Systems Engineering and Decision Making Models},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD},
year={2017},
pages={147-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006485201470154},
isbn={978-989-758-272-1},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD
TI - Modelling Decision Support Systems using Conceptual Constraints - Linking Process Systems Engineering and Decision Making Models
SN - 978-989-758-272-1
IS - 2184-3228
AU - Dombayci, C.
AU - Espuña, A.
PY - 2017
SP - 147
EP - 154
DO - 10.5220/0006485201470154
PB - SciTePress