Balázs Hidasi

The Contextual Turn

2016

A critical change has occurred in the status of context in recommender systems. In the past, context has been considered 'additional evidence'. This past picture is at odds with many present application domains, where user …

Multimedia recommender systems

2018

This tutorial introduces multimedia recommender systems (MMRS), in particular, recommender systems that leverage multimedia content to recommend different media types. In contrast to the still most frequently adopted collaborative filtering approaches, we focus on content-based …

Session-based Recommendations with Recurrent Neural Networks

2015 · arXiv (Cornell University)

We apply recurrent neural networks (RNN) on a new domain, namely recommender systems. Real-life recommender systems often face the problem of having to base recommendations only on short session-based data (e.g. a small sportsware website) …

Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations

2016

Real-life recommender systems often face the daunting task of providing recommendations based only on the clicks of a user session. Methods that rely on user profiles -- such as matrix factorization -- perform very poorly …

Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks

2017

Session-based recommendations are highly relevant in many modern on-line services (e.g. e-commerce, video streaming) and recommendation settings. Recently, Recurrent Neural Networks have been shown to perform very well in session-based settings. While in many session-based …

Recurrent Neural Networks with Top-k Gains for Session-based Recommendations

2018

RNNs have been shown to be excellent models for sequential data and in particular for data that is generated by users in an session-based manner. The use of RNNs provides impressive performance benefits over classical …