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Critiquing-based recommenders: survey and emerging trends

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Collaborative Recurrent Neural Networks for Dynamic Recommender Systems

Matthias Grossglauser, Lucas Maystre, Young Jun Ko

Modern technologies enable us to record sequences of online user activity at an unprecedented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating-prediction paradigm, ignoring temporal ...

2016

Social Interface and Interaction Design for Group Recommender Systems

Yu Chen

Group recommender systems suggest items of interest to a group of people. Traditionally, group recommenders provide recommendations by aggregation the group membersâ preferences. Nowadays, there is a trend of decentralized group recommendation process th ...

EPFL2015

MEM0R1ES: Memory-based Information Systems

Michele Catasta

The advent of the Web reshaped the way in which humans memorize information, arguably unlike any other technological advance of the last decades. Rather than remembering the information itself, people are primed to find the needed information through Web s ...

EPFL2015

Distributed user profiling via spectral methods

Dan-Cristian Tomozei

User profiling is a useful primitive for constructing personalised services, such as content recommendation. In the present paper we investigate the feasibility of user profiling in a distributed setting, with no central authority and only local informatio ...

2014

Comparing the Predictive Capability of Social and Interest Affinity for Recommendations

Karl Aberer, Anne-Marie Kermarrec, Alexandra Olteanu

The advent of online social networks created new prediction opportunities for recommender systems: instead of relying on past rating history through the use of collaborative filtering (CF), they can leverage the social relations among users as a predictor ...

Springer-Verlag Berlin2014

Recommendation using textual opinions

Boi Faltings, Claudiu-Cristian Musat

Many web sites collect reviews of products and services and use them provide rankings of their quality. However, such rankings are not personalized. We investigate how the information in the reviews written by a particular user can be used to personalize t ...

2013

Design and User Perception Issues for Personality-Engaged Recommender Systems

Rong Hu

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

A User-Centric Evaluation Framework for Recommender Systems

Pearl Pu Faltings, Li Chen, Rong Hu

This research was motivated by our interest in understanding the criteria for measuring the success of a recommender system from users’ point view. Even though existing work has suggested a wide range of criteria, the consistency and validity of the combin ...

2011

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

User interaction with online geospatial systems

Jens Ingensand

User interaction with online geospatial systems is an inter-disciplinary research field that combines the two disciplines Human Computer Interaction (HCI) and geographic information sciences. In recent years online geospatial systems have been created for ...

EPFL2010