Concept

Filtrage collaboratif

Publications associées (117)

Neighborhood-based Tag Prediction

Karl Aberer, Philippe Cudré-Mauroux, Sebastian Michel, Adriana Budura

We consider the problem of tag prediction in collaborative tagging systems where users share and annotate resources on the Web. We put forward HAMLET, a novel approach to automatically propagate tags along the edges of a graph which relates similar documen ...

2009

Rating aggregation in collaborative filtering systems

Boi Faltings, Radu Jurca, Florent Frédéric Garcin, Nadine Joswig

Recommender systems based on user feedback rank items by aggregating users' ratings in order to select those that are ranked highest. Ratings are usually aggregated using a weighted arithmetic mean. However, the mean is quite sensitive to outliers and bias ...

ACM Press2009

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

Online Piece-wise Linear Approximation of Numerical Streams with Precision Guarantees

Willy Zwaenepoel, Emmanuel Cecchet

Continuous "always-on" monitoring is beneficial for a number of applications, but potentially imposes a high load in terms of communication, storage and power consumption when a large number of variables need to be monitored. We introduce two new filtering ...

2009

Who is the expert? analyzing gaze data to predict expertise level in collaborative applications

Pierre Dillenbourg, Mirweis Sangin, Marc-Antoine Nüssli, Yuan Liu, Yan Liu

In this paper, we analyze complex gaze tracking data in a collaborative task and apply machine learning models to automatically predict skill-level differences between participants. Specifically, we present findings that address the two primary challenges ...

IEEE Press2009

Teaching Physical Collaborative Tasks: Object-Lifting Case Study with a Humanoid

Aude Billard, Sylvain Calinon, Elena Gribovskaya

This paper presents the application of a statistical framework that allows to endow a humanoid robot with the ability to perform a collaborative manipulation task with a human operator. We investigate to what extent the dynamics of the motion and the hapti ...

IEEE2009

How Users Perceive and Appraise Personalized Recommendations

Pearl Pu Faltings, Li Chen, Nicolas Jones

Traditional websites have long relied on users revealing their preferences explicitly through direct manipulation interfaces. However recent recommender systems have gone as far as using implicit feedback indicators to understand users' interests. More tha ...

Springer2009

How Users Perceive and Appraise Personalised Recommendations

Chen Li

2009

User Acceptance Issues in Music Recommender Systems

Pearl Pu Faltings, Nicolas Jones

Two music recommender systems were compared side-by-side in an in- depth between-subject lab study. The main objectives were to investigate users' acceptance of music recommendations and to probe the main technology acceptance model in the environment of l ...

2008

Physical-virtual linkage with contextual bookmarks

Xavier Righetti

In our everyday life we often see objects or persons and are aware that there are related digital services such as an online ticket service when seeing a poster advertising a concert. Currently it is a rather time consuming activity to find the related inf ...

ACM Press2008

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