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Collaborative Recurrent Neural Networks for Dynamic Recommender Systems

Publications associées (57)

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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

Aggregating information from the crowd

Florent Frédéric Garcin

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

User Profiling Using Submitted Review Content

Boi Faltings, Claudiu-Cristian Musat, Yizhong Liang

A computer-implemented method for generating a user profile of a user of an online platform, a computer-implemented method for providing a first user with targeted information and a computer-implemented method for providing a user of an online platform wit ...

2014

CoFeed: privacy-preserving Web search recommendation based on collaborative aggregation of interest feedback

Martin Rajman, Vinh Toan Luu, Pascal Felber

Search engines essentially rely on the structure of the graph of hyperlinks. Although accurate for the main trend, this is not effective when some query is ambiguous. Leveraging semantic information by the mean of interest matching allows proposing complem ...

Wiley-Blackwell2013

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

A Survey on Language Modeling using Neural Networks

Nikolaos Pappas, Thomas Meyer

A Language Model (LM) is a helpful component of a variety of Natural Language Processing (NLP) systems today. For speech recognition, machine translation, information retrieval, word sense disambiguation etc., the contribution of an LM is to provide featur ...

Idiap2012

Critiquing-based recommenders: survey and emerging trends

Pearl Pu Faltings, Li Chen

Critiquing-based recommender systems elicit users' feedback, called critiques, which they made on the recommended items. This conversational style of interaction is in contract to the standard model where users receive recommendations in a single interacti ...

2012

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

Trust-Based Rating Prediction for Recommendation in Web 2.0 Collaborative Learning Social Software

Denis Gillet, Na Li

Benefiting from the advent of social software, information sharing becomes pervasive. Personalized rating systems have emerged to evaluate the quality of user-generated content in open environment and provide recommendation based on users’ past experience. ...

2010

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