Recommendation engine for intelligent recruiting and expertise matching using social media-like deep collaborative filtering

In today’s candidate-driven market, talent recruitment represents a major challenge for many companies. Younger millennials have different expectations of their work environment than previous generations. They are heavy users of technology in almost all their activities, including job search. They are also used to multiple social medias and expect faster feedback. In this changing environment, traditional job web sites do not answer the challenges facing today’s talent recruitment. It becomes obvious that we need a new approach to tackle this problem. Using social medias like models in recruitment is a new idea that can have a positive impact in today’s job market. The goal here is to develop advanced machine-learning algorithms, that can learn and improve over time, for a recommender system candidate-company matching in the context of recruitment.

Faculty Supervisor:

Moulay Akhloufic

Student:

Abdarahmane Traoré

Partner:

GradsFinder Recruiting Inc

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Université de Moncton