Z-ENG: Machine Learning in Recommender Systems

Félév: 2024-2025 ősz

Kategória: Nincs megadva

Téma leírása

The topic is available also in Hungarian

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. Another option is to involve modern reinforcement learning techniques. The student will work on the elaboration and evaluation of such a technique, e.g., with a custom RNN.

For details, see:

• Predictive techniques:
  https://arxiv.org/pdf/2004.13715.pdf, Section 4.1.

• Reinforcement learning techniques: https://arxiv.org/pdf/1801.00209.pdf

Maximális létszám: 6 fő