The Architecture of the Intelligent Case-Based Reasoning Recommender System (CBR RS) Recommending Preventive/Corrective Procedures in the Occupational Health and Safety Management System in an Enterprise
The Architecture of the Intelligent Case-Based Reasoning Recommender System (CBR RS) Recommending Preventive/Corrective Procedures in the Occupational Health and Safety Management System in an Enterprise

Summary/Abstract: The paper presents the original architecture of the system recommending preventive/corrective procedures in the occupational health and safety management system in an enterprise: ComplianceOHS-CBR. The system consists of four modules: Module A — an ontology of the workplace OHS profile, Module B — an ontology of preventive/corrective procedure indexation OPCPI, Module C — a recording system of the monitoring process of non-compliance with the requirements of OHS, and Module D — a recommending engine consistent with the CBR methodology. The essence of the approach presented in this paper is the integration of the monitoring system of the analysis process of non-compliance with OHS requirements at the workplace (using the ADONIS system) with the case-based reasoning process (CBR). The integration platform consists of two ontologies: an ontology of profile compliance with the workplace OHS requirements (OP-OHS) and an ontology of preventive/corrective procedure indexation (OPCPI). Both of the ontologies are presented in the Protege 5 OWL editor. Inference engines are alternatively, according to the CBR methodology, myCBR and jCOLLIBRI.

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