Appliciation of Transfer Learning for cross domain recommendation system

Use cross domian transfer learning for recommendations

抄録

In the big data era, a good Machine learning model requires massive training data with labels. When there is less data available in a target domain, Cross-domain recommendations are useful to leverage richer data from a source domain to improve performance of the recommendation. Cross-domain recommendation has gained lots of interest in recent years. In this talk, we will talk about the overview of CDR, what are the existing CDR approaches, demonstrate a hands-on application for user profile prediction using CDR, as well as the challenges and future directions.