Seminar: A Personalized Course Recommendation System Based on Career Goals
M.Sc. Thesis Proposal
Supervisor: Dr. Wolfgang Banzhaf
A Personalized Course Recommendation System Based on Career Goals
Department of Computer Science
Thursday, January 28, 2016, 2:40 p.m., Room EN 2022
Recommender systems have become very popular and are integrated into many applications that we use everyday. We are recommended music pieces, articles, books, movies and many other things of daily life by many websites. Education is another example of a domain where recommender systems can help make better and wiser decision that affect the future. With the growing number of available courses online, it is a serious problem of how to choose the right courses. In this thesis, a new recommendation
system for courses is proposed that takes the user’s career goals into consideration in order to help them with choosing the right path toward their goals. The system will use the data from LinkedIn professional social network. Public profiles of people with desired career goals and their top skills will be extracted in order to form the data set. Then with the use of association rule mining and genetic algorithm, best rules will be evolved in order to show which skills are necessary for each career goal. Then with the use of a set of data extracted from course descriptions, a table will be generated showing the associations between skills and courses. With the use of the extracted data set from LinkedIn, associations between each skill and courses, and a minimization algorithm for finding minimum number of effective courses, the system will hopefully be able to recommend courses to the users in order to help users achieve their career targets faster.