Maksims Volkovs

Context Models For Web Search Personalization

2015 · arXiv (Cornell University)

We present our solution to the Yandex Personalized Web Search Challenge. The aim of this challenge was to use the historical search logs to personalize top-N document rankings for a set of test users. We …

TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations

2020

Collaborative filtering with implicit feedback is a ubiquitous class of recommendation problems where only positive interactions such as purchases or clicks are observed. Autoencoder-based recommendation models have shown strong performance on many implicit feedback benchmarks. …

DropoutNet: Addressing Cold Start in Recommender Systems

2017 · Neural Information Processing Systems

Latent models have become the default choice for recommender systems due to their performance and scalability. However, research in this area has primarily focused on modeling user-item interactions, and few latent models have been developed …

Content-based Neighbor Models for Cold Start in Recommender Systems

2017

Cold start remains a prominent problem in recommender systems. While rich content information is often available for both users and items few existing models can fully exploit it for personalization. Slow progress in this area …