An Intelligent Multi-Agent Recommender System for Human Capacity Building

Details An Intelligent Multi-Agent Recommender System for Human Capacity Building An Intelligent Multi-Agent Recommender System for Human Capacity Building

2008-06-13

arxiv.org/abs/0806.2216v1

Computer Science

Artificial Intelligence

Proceedings of the 14th IEEE Mediterranean Electrotechnical Conference, 2008, pages 909 to 915

Scientific paper

This paper presents a Multi-Agent approach to the problem of recommending training courses to engineering professionals. The recommendation system is built as a proof of concept and limited to the electrical and mechanical engineering disciplines. Through user modelling and data collection from a survey, collaborative filtering recommendation is implemented using intelligent agents. The agents work together in recommending meaningful training courses and updating the course information. The system uses a users profile and keywords from courses to rank courses. A ranking accuracy for courses of 90% is achieved while flexibility is achieved using an agent that retrieves information autonomously using data mining techniques from websites. This manner of recommendation is scalable and adaptable. Further improvements can be made using clustering and recording user feedback.

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