Argumentation graphs with constraint-based reasoning for collaborative expertise

Doumbouya, Mamadou Bilo; Kamsu-Foguem, Bernard; Kenfack, Hugues; Foguem, Clovis

doi:10.1016/j.future.2017.09.081

Cited by 11 publications

(6 citation statements)

References 30 publications

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“…Indeed, on the one hand, it allows the formalization of conceptual and inferential knowledge of a target domain. On the other hand, the provided reasoning tools facilitate the visualization, the enrichment and the verification of the modelled knowledge by end users (Doumbouya, Kamsu-Foguem, Kenfack & Foguem, 2018;Kamsu-Foguem & Tiako, 2017;Doumbouya, Kamsu-Foguem, Kenfack & Foguem, 2015;Kamsu-Foguem & Abanda, 2015;Kamsu-Foguem, Tchuenté-Foguem, & Foguem, 2014;Kamsu-Foguem, Diallo, & Foguem, 2013;Potes Ruiz, Kamsu-Foguem & Noyes, 2013;Kamsu Foguem, Coudert, Béler & Geneste, 2008;Kamsu-Foguem & Chapurlat, 2006;Chein, Mugnier, & Croitoru, 2013). In the context of the semantic web, the conceptual graphs can play a pivotal role for some knowledge representation languages, while ensuring the interoperability and the complementarity of modes of reasoning.…”

Section: Semantic Modelling With Conceptual Graphsmentioning

confidence: 99%

Graph-based ontology reasoning for formal verification of BREEAM rules

Kamsu-Foguem¹,

Abanda²,

Doumbouya³

et al. 2019

Cognitive Systems Research

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Section: Semantic Modelling With Conceptual Graphsmentioning

confidence: 99%

Graph-based ontology reasoning for formal verification of BREEAM rules

Kamsu-Foguem¹,

Abanda²,

Doumbouya³

et al. 2019

Cognitive Systems Research

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“…To overcome the inconsistencies, first the arguments evolving in the argumentation system are weighted on the basis of the competencies of the health professionals and the credibility of the sources justifying their advice, and second some law concepts are modelled as constraints in order to check their compliance of the collaborative process. As limit of this work, the health professionals’ advice should be weighting automatically during collaborative medical practices [39]. Always in the medical domain, a new technique supported by graphical reasoning is proposed in Doumbouya et al [40] in order to formalise elements of argumentation in collaborative medical organisations using telemedicine.…”

Section: Related Workmentioning

confidence: 99%

A knowledge-based model for managing the ontology evolution: case study of maintenance in SONATRACH

Sad-Houari

Taghezout

Nador

2018

Journal of Information Science

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The challenges of the development of a suitable ontology scheme in decision-making environment should be taken in conjunction with the exploitation of more recent technologies. It is expected that the use of ontologies will lead to the construction of more intelligent applications, allowing them to work more specifically at a human conceptual level. We propose in this article an approach that analyses the impact of changes in the ontology on business rules in order to detect inconsistencies that may be generated. In addition, the developed tool provides solutions to repair inconsistencies with the help of domain experts. In our work, business rules are edited from the concepts and properties that are stored in an OWL (Web Ontology Language) ontology named OntoloG. This latter is implemented throughout the use of Protégé 4.0.2.with the OWL sub-language. OntoloG has been developed by the knowledge acquisition from documents, collection and capitalisation of business rules process with experts in SONATRACH AVAL.

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“…Thus we add the concepts Inputs, Outputs, Preconditions to manage the dependence between actions (Fig. 7) (Doumbouya, Kamsu-Foguem, Kenfack, & Foguem, 2018;Saadati & Denker, 2010).…”

Section: Conceptual Levelmentioning

confidence: 99%

Discovering frequent patterns for in-flight incidents

Sene

Kamsu-Foguem

Rumeau

2018

Cognitive Systems Research

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Objectives: In order to get a clearer idea of in-flight medical emergencies management, the application of Data mining tools can be useful to facilitate knowledge discovery from data collected by existing studies. The objective of this work is to conceptualize the construction of a Clinical Decision Support System (CDSS) in three stages corresponding to the representation levels necessary to extract knowledge from information and raw data. Method: The method can be summarized in three parts: (1) in-flight medical incident data search, (2) the validation of this data using Data mining tools, (3) the construction of the CDSS in 3 steps corresponding to the levels of knowledge representation. These three steps will be carried out using tools such as EORCA (Event Oriented Representation for Collaborative Activities) which includes action codification with regard to an ontology and event representation. Result: Data processing services provide a good structuration for information about in-flight medical incidents from which useful knowledge can be generated could improve the handling of other incidents by adapting the medical emergency equipments, for example. This structuring can be facilitated by the use of CDSS to fill in any gaps, increase coherency, and provide decision makers with a more complete picture of options that might be involved in a critical situation. Conclusion: We proposed an evolving framework facilitating the description of in-flight medical emergencies with adequate data collection and appropriate information that are required for producing interesting rules and better decisions. The data collected nourishes the organization of information, which can be improved over time by continuous integration of evidence gained from the number of incidents treated. Finally, it is proposed to strengthen requirements concerning the medical equipments available on-board, particularly in the light of knowledge resulting from the selection and approval of interesting rules.

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Argumentation graphs with constraint-based reasoning for collaborative expertise

Cited by 11 publications

References 30 publications

Graph-based ontology reasoning for formal verification of BREEAM rules

Graph-based ontology reasoning for formal verification of BREEAM rules

A knowledge-based model for managing the ontology evolution: case study of maintenance in SONATRACH

Discovering frequent patterns for in-flight incidents

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