Intelligent Course Recommender for Professional Development

Abstract

One of the major challenges faced in oil and gas industry today is talent management of its workforce. Training the workforce and suggesting the right training courses to the individuals is important in talent management and career development. There are many training recommendation systems available using different machine learning approaches such as collaborative filtering, neural networks and hybrid models. In this paper, an intelligent recommendation system is proposed by blending machine learning algorithms, natural language processing (NLP) and text analytics combined with organizational preferences. This framework gives a recommender system considering the user profiles, training preferences for his or her organization where each set of organizational units will have unique training recommendation requirements considering organizational functional behavior. The proposed mechanism uses machine learning algorithms at different stages of its learning process and ensemble them in a unique fashion such that desirable results are achieved to the user satisfaction.