Deep into recommendation based product ranking
In a world where businesses offer hundreds of products, and customers have limited time for exploration, recommendation systems make the difference between providers of similar products. While early studies into product recommendation target systems based on explicit feedback, with the expanse of big data, the usage of implicit feedback becomes vital. In this talk I will focus on different methods for data representation, algorithmic approaches for building product recommendations, as well as model evaluation.
Iulia Pasov is a senior Data Scientist working for Sixt SE, as well as a PhD student in Artificial Intelligence and Psychology and a WiDS Ambassador. As a Data Scientist, Iulia focuses on building AI-based services meant to optimize car rental processes, as well as pipelines for automatic training and deploying of machine learning models. For her studies, she searches ways to improve learning in online knowledge building communities with the use of artificial intelligence.