Discover how graph algorithms are transforming content recommendation in this insightful talk. We'll journey from the basics of graph-based models, exploring simple graph walks, to the cutting-edge realm of Graph Neural Networks. Uncover the power of graph embeddings and learn when graph-based approaches excel in recommender systems.
Dr. Mirza Klimenta
Mirza Klimenta received his PhD in Computer Science from the University of Konstanz (Germany) at age 25. While in academia, Mirza worked in the fields of dimension reduction and graph embedding, and his work has been recognized by the scientific community. As a (Senior) Data Scientist, Mirza focuses on Recommender Systems and Algorithm Engineering. His most notable work is in the design and implementation of a Recommender System powering ARD Audiothek, one of the most popular audio-on-demand platforms in Germany. He is also a writer of literary fiction.
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