A Hybrid Training Course Recommender System using Case-based Reasoning and Fuzzy Logic

Abstract

In this study, firstly two challenges ahead of SMEs in doing need assessment & educational planning are considered. Then the issue of finding and selecting training courses is elaborated. Afterwards, a system of recommending training courses using case-based reasoning and Fuzzy Model is presented in order to identify the need assessment of firms as well as planning a suitable curriculum. The case-based reasoning is based on this principle that similar problems have similar solutions. In the knowledge base (case base) of this methodology in which the information & records of the past are gathered as cases, helps to collect & maintain the experts' knowledge in the proposed system. In this system, the Fuzzy model has been used to cope with the ambiguities & uncertainties in case representation and retrieval phase. EFQM (European Foundation for Quality Management) is applied for case modeling. Besides, in order to overcome the cold start problem, a module that is called SMART (Supplementary Module to Accomplish Recommending Task) has been used in which infer as an expert. Finally, this system is evaluated and the results are reported.

Keywords

• need assessment
• training course recommendation
• recommender system
• case-based reasoning
• fuzzy logic
• small and medium enterprises (smes)