Paolo Cremonesi

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 …

Methodological Issues in Recommender Systems Research (Extended Abstract)

2020

The development of continuously improved machine learning algorithms for personalized item ranking lies at the core of today's research in the area of recommender systems. Over the years, the research community has developed widely-agreed best …

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 …

Sequence-Aware Recommender Systems

2018 · ACM Computing Surveys

Recommender systems are one of the most successful applications of data mining and machine-learning technology in practice. Academic research in the field is historically often based on the matrix completion problem formulation, where for each …

Movie genome: alleviating new item cold start in movie recommendation

2019 · User Modeling and User-Adapted Interaction

As of today, most movie recommendation services base their recommendations on collaborative filtering (CF) and/or content-based filtering (CBF) models that use metadata (e.g., genre or cast). In most video-on-demand and streaming services, however, new movies …

Are we really making much progress? A worrying analysis of recent neural recommendation approaches

2019

Deep learning techniques have become the method of choice for researchers working on algorithmic aspects of recommender systems. With the strongly increased interest in machine learning in general, it has, as a result, become difficult …

Recommender Systems Leveraging Multimedia Content

2020 · ACM Computing Surveys

Recommender systems have become a popular and effective means to manage the ever-increasing amount of multimedia content available today and to help users discover interesting new items. Today’s recommender systems suggest items of various media …