Related Pins is the Web-scale recommender system that powers over 40% of user
engagement on Pinterest. This paper is a longitudinal study of three years of its …

User experience in modern content discovery applications critically depends on high-quality
personalized recommendations. However, building systems that provide such …

Sequential models that encode user activity for next action prediction have become a
popular design choice for building web-scale personalized recommendation systems …

In this work, we present our journey to revolutionize the personalized recommendation
engine through end-to-end learning from raw user actions. We encode user's long-term …

Recommender systems research is being slowed by the difficulty of replicating and
comparing research results. Published research uses various experimental methodologies …

With the increasing demand for deeper understanding of users» preferences, recommender
systems have gone beyond simple user-item filtering and are increasingly sophisticated …

Over the past three years Pinterest has experimented with several visual search and
recommendation systems, from enhancing existing products such as Related Pins (2014), to …

Latent user representations are widely adopted in the tech industry for powering
personalized recommender systems. Most prior work infers a single high dimensional …

When the Netflix Prize launched in 2006, it put a spotlight on the importance and use of
recommender systems in real-world applications. The competition provided many lessons …

Recommender Systems are a prime example of the mainstream industry use of large-scale
machine learning and data mining. Diverse applications in areas such as e-commerce …