Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
As online stores are offering an almost unlimited shelf space, users must increasingly rely on product search and recommender systems to find their most preferred products and decide which item is the truly best one to buy. However, much research work has ...
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 ...
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
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 ...
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
Conversational recommenders can help users find their most preferred item among a large range of options, a task that we call preference-based search. ...
Online systems that help users select the most preferential item from a large electronic catalog are known as product search and recommender systems. Evaluation of various proposed technologies is essential for further development in this area. This paper ...
This user manual's purpose is to help the user to get familiar with the miniature suscep- tometer (MSM) and to allow them to make use of it in the most conscious manner. It also contains instructions and advice on the last tasks to be done before putting t ...
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 ...
