Engineering pathway for user personal knowledge recommendation

Abstract

K-Gray Engineering Pathway (EP) is a Digital library website that allows search and catalog of engineering education and computer science education resources for higher education and k-12 educators and students. In this paper, we propose a new EP that can give different and personal search recommendation for users with different educational background and accomplish this function automatically. For data, we explore semantic relationships among knowledge, and then we classify them and establish the knowledge relationships model. For users, we can set up user profile by user log, then classify them and establish user model. When a frequent user come to EP looking for something, we can give information directly related and recommend knowledge not directly related but can arouse their interest, based on these two models. The experiments shows that we make EP a more excellent expert who know users well enough to guide them, according to the statistic information such as education background, and by improving the collaborative recommend results in EP, our users can make the best use of their time by EP learning. © 2012 Springer-Verlag.