Predicting Personalized Academic and Career Roads: First Steps Toward a Multi-Uses Recommender System
This addresses the challenge of personalized career and education planning for individuals, but appears incremental as it builds on existing recommender system approaches.
The paper tackles the problem of predicting personalized academic and career paths by introducing concepts representing fields of study or job domains to model users' future trajectories, showing how these concepts influence predictions when recommending next steps.
Nobody knows what one's do in the future and everyone will have had a different answer to the question : how do you see yourself in five years after your current job/diploma? In this paper we introduce concepts, large categories of fields of studies or job domains in order to represent the vision of the future of the user's trajectory. Then, we show how they can influence the prediction when proposing him a set of next steps to take.