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Positive and Negative Critiquing for VAE-based Recommenders

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With an ever-growing amount of data generated on the web, aggregating information from the crowd into meaningful knowledge has become crucial to companies in order to create a competitive edge. Not only companies, but also organizations and governments can ...

EPFL2014

HyRec: leveraging browsers for scalable recommenders

Rachid Guerraoui, Anne-Marie Kermarrec, Davide Frey, Rhicheek Patra

The ever-growing amount of data available on the Internet calls for personalization. Yet, the most effective personalization schemes, such as those based on collaborative filtering (CF), are notoriously resource greedy. This paper presents HyRec, an online ...

ACM2014

Recommender systems have emerged, as an intelligent information filtering tool, to help users effectively identify information items of interest from a set of overwhelming choices and provide personalized services. Most recommendation technologies typicall ...

EPFL2012

Music Recommendation to Groups

Lucas Maystre

First we present Unison, a conceptual music recommender system for groups of people; the system aims at generating a playlist that takes musical tastes of all the group members into account. We discuss both theoretical and practical concerns related to suc ...

2012

User Perceived Qualities and Acceptance of Recommender Systems

Nicolas Jones

Recommender systems have become important, as users are faced with an ever-increasing amount of information available on internet. Much of the research work on the topic has been focused on recommendation techniques, aiming at improving the accuracy of rec ...

EPFL2010

A Study on User Perception of Personality-Based Recommender Systems

Pearl Pu Faltings, Rong Hu

Our previous research indicates that using personality quizzes is a viable and promising way to build user profiles to recommend entertainment products. Based on these findings, our current research further investigates the feasibility of using personality ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2010

Preserving Privacy in Collaborative Filtering through Distributed Aggregation of Offline Profiles

Jean-Pierre Hubaux, Reza Shokri, Georgios Theodorakopoulos, Pedram Pedarsani

In recommender systems, usually, a central server needs to have access to users' profiles in order to generate useful recommendations. Having this access, however, undermines the users' privacy. The more information is revealed to the server on the user-it ...

ACM2009

Ontology filtering

Vincent Jean Fabrice Schickel

With the ever growing importance of internet, people are becoming overwhelmed by information. More concretely, consider a situation where you find yourself with an evening alone and would like to rent a DVD to watch. For several reasons, this is a difficul ...

EPFL2007