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Towards Graph Foundation Models for Personalization
Andreas Damianou, Francesco Fabbri, Paul Gigioli +4
In the realm of personalization, integrating diverse information sources such as consumption signals and content-based representations is becoming increasingly critical to build st…
Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks
Marco De Nadai, Francesco Fabbri, Paul Gigioli +11
In the ever-evolving digital audio landscape, Spotify, well-known for its music and talk content, has recently introduced audiobooks to its vast user base. While promising, this mo…
Improving Content Retrievability in Search with Controllable Query Generation
Gustavo Penha, Enrico Palumbo, Maryam Aziz +2
An important goal of online platforms is to enable content discovery, i.e. allow users to find a catalog entity they were not familiar with. A pre-requisite to discover an entity,…
Episodes Discovery Recommendation with Multi-Source Augmentations
Ziwei Fan, Alice Wang, Zahra Nazari
Recommender systems (RS) commonly retrieve potential candidate items for users from a massive number of items by modeling user interests based on historical interactions. However,…
Sequential Recommendation via Stochastic Self-Attention
Ziwei Fan, Zhiwei Liu, Alice Wang +4
Sequential recommendation models the dynamics of a user's previous behaviors in order to forecast the next item, and has drawn a lot of attention. Transformer-based approaches, whi…