Václav Blahut

Václav Blahut, a machine learning researcher at Seznam.cz, dives into the intricate world of personalized news recommendations. He highlights the challenges of popularity bias, explaining how it can skew user exposure toward trending content while neglecting niche interests. Václav introduces the concept of inverse recommendation, where the focus shifts to finding the right users for less popular items. He discusses strategies to balance diversity and business metrics and emphasizes the importance of adapting user profiles through multiple embeddings for a more personalized experience.