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.
Users' critiques to the current recommendation form a crucial feedback mechanism for refining their preference models and improving a system's accuracy in recommendations that may better interest the user. In this paper, we present a novel approach to assi ...
A recommender system's ability to establish trust with users and convince them of its recommendations, such as which camera or PC to purchase, is a crucial design factor especially for e-commerce environments. This observation led us to build a trust model ...
Two music recommender websites, Pandora (a content-based recommender) and Last.fm (a rating-based social recommender), were compared side-by-side in a within-subject user study involving 64 participants. The main objective was to investigate users’ initial ...
We propose a novel critiquing-based recommender interface, the hybrid critiquing interface that integrates the user self-motivated critiquing facility to compensate for the limitations of system-proposed critiques. The results from our user study show that ...
Association for Computing Machinery, New York, NY 10036-5701, United States2007
In many interactive decision making scenarios there is often no solution that satisfies all of the user's preferences. The decision process can be helped by providing explanations. Relaxations show sets of consistent preferences and, thus, indicate which p ...
American Association for Artificial Intelligence, Menlo Park, CA 94025-3496, United States2007
Conversational recommenders can help users find their most preferred item among a large range of options, a task that we call preference-based search. ...
Conversational recommender systems are designed to help users to more efficiently navigate complex product spaces by alternatively making recommendations and inviting users' feedback. Compound critiquing techniques provide an efficient way for users to fee ...
Association for Computing Machinery, New York, NY 10036-5701, United States2007
We describe a user study evaluating two critiquing-based recommender agents based on three criteria: decision accuracy, decision effort, and user confidence. Results show that user-motivated critiques were more frequently applied and the example critiquing ...
American Association for Artificial Intelligence, Menlo Park, CA 94025-3496, United States2006
Compound critiques allow users to simultaneously express directional preferences over several product attributes. Presenting the user with compound critiques is not a new idea. The original Find-Me Systems (e.g., Car Navigator) showed static compound criti ...
Association for Computing Machinery, New York, NY 10036-5701, United States2007
Preference-based search (PBS) is a popular approach for helping consumers find their desired items from online catalogs. Currently most PBS tools generate search results by a certain set of criteria based on preferences elicited from the current user durin ...
Association for Computing Machinery, New York, NY 10036-5701, United States2007