Z-ENG: RNN based Recommender
The primary goal of recommender systems is to estimate user preferences on items, e.g., audio, video content. Such systems are applied by various online companies, e.g., Google, Bing, YouTube, Amazon, eBay, Booking. A relatively novel approach to calculate recommendations is the session-based recommendation technique. In this case, an RNN is applied to predict the next item that can be interesting for a particular user.
The student will work on the elaboration and evaluation of such a technique, e.g., with a custom RNN. For details on predictive techniques, see: https://arxiv.org/pdf/2004.13715.pdf, Section 4.1.