A Decision Support System Based on Ontology Learning from PMI’ Project Risk Management

Zaouga, Wiem; Rabai, Latifa Ben Arfa

doi:10.1007/978-3-030-71187-0_67

Cited by 1 publication

(1 citation statement)

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“…We draw the conclusion that more research based on coordinating techniques between agents is required given this and the fact that interaction capacities are crucial for web DSS to operate in its (anytime, anywhere) deployment mode. To enhance the assistance for decision-making and organizing operations, the contextual data domain provided in the software tool will be expanded especially [13].…”

Section: Introductionmentioning

confidence: 99%

Systematic Review of Web-Based Decision Support Systems for Clinical Applications: Enhancing Ontology with Unified Modeling Language and Ontology Web Language

Ahmed,

Layeb

2024

TEM Journal

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This article demonstrates an ontology-based technique that aids in envisioning the problem domain before software development, presenting an approach to assist decision-making for reliable and optimal healthcare administration. The proposed approach is designed for utilization by a Web-Based Decision Support System (WebDSS). The purpose of the study is to aid readers in comprehending how ontologies in healthcare management platforms can be modeled using UML and OWL. For the conceptualization and the design, service modelling and the semantics of the web language are crucial. We demonstrate the use of the Unified Modeling Language (UML) and the Ontology Web Language (OWL) in the administration of healthcare operations and key elements of the model-base of healthcare administration systems. Highly educated systems with automated assistance will allow decision-makers to more effectively incorporate aspects of sustainability into their decisions. In order to generate semantic ontologies for medical management, the present study proposes an ontology creation technique and a Semantic Web framework called Protégé. Web-based technologies, decision trees, data mining, and computational algorithms are implemented by WebDSS to assess medical resources administration information in real-time. These methods are employed to develop a decision making framework for this study. Time series graphs, email reports, and webpages are used to display the test findings. When healthcare thresholds are surpassed, the system uses text messages as email reports to automatically deliver warnings. Our study's primary contribution is the creation of a useful tool that makes it easier for academics studying medical concerns to locate online sites with information.

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Section: Introductionmentioning

confidence: 99%