Publication

Experiments on the Preference-Based Organization Interface in Recommender Systems

Publications associées (62)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

User-based evaluation of an interactive expert system for full-year daylighting design support

Marilyne Andersen

This paper presents the results of an original design process-oriented user study conducted on an interactive expert system specifically developed for full year, climate-based daylighting design support. The aim of the study was to determine how well its d ...

2012

Analyzing User Patterns to Derive Design Guidelines for Job Seeking and Recruiting Website

Yao Lu

More and more competitive websites are targeting online job seeking and recruiting. In this paper, we discuss user pattern in an online job seeking website in Switzerland, by analyzing user profiles and actions. Then based on our findings, we derive design ...

IARIA, 20122012

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

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

HEAT: Iterative Relevance Feedback with One Million Images

François Fleuret, Nicolae Suditu

It has been shown repeatedly that iterative relevance feedback is a very efficient solution for content-based image retrieval. However, no existing system scales gracefully to hundreds of thousands or millions of images. We present a new approach dubbed Hi ...

2011

HEAT: Iterative Relevance Feedback with One Million Images

François Fleuret, Nicolae Suditu

Idiap2011

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

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

Eye-Tracking Product Recommenders' Usage

Pearl Pu Faltings, Nicolas Jones

Recommender systems have emerged as an effective decision tool to help users more easily and quickly find products that they prefer, especially in e-commerce environments. However, few studies have tried to understand how this technology has influenced the ...

ACM2010

The 3A Personalized, Contextual and Relation-based Recommender System

Denis Gillet, Christophe Salzmann

This paper discusses the 3A recommender system that targets CSCL (computer-supported collaborative learning) and CSCW (computer-supported collaborative work) environments. The proposed system models user interactions in a heterogeneous graph. Then, it appl ...

2010