From Decision Support Systems to Recommender Systems
Pascale Zaraté | Institut de Recherche en Informatique de Toulouse, France
Decision Support Systems are designed to support decision makers facing unstructured problems. They were developed to interactively simulate the problem in order to propose to the user part of the solution. Recently, they have evolved into recommender systems, for which a user profile is defined. Recommender systems aim at mining users’ preferences dynamically, in order to propose to the decision makers solutions which are as near as possible to their needs. For this purpose, machine learning techniques are applied.
Pascale Zaraté is Professor at Toulouse 1 Capitole University, and conducts her research at the IRIT laboratory ( She holds a Ph.D. in Computer Science / Decision Support from the LAMSADE laboratory at the Paris Dauphine University, Paris (1991) and a “Habilitation to Conduct Research” in Computer Science / Cooperative Decision Support from the IRIT laboratory at INPT, Toulouse (2005). Pascale Zaraté’s current research interests include: Decision Support Systems; Group Decision Support Systems; Cooperative Decision Making. She is the editor-in-chief of the International Journal of Decision Support Systems Technologies (Ed IGI Global).
Contact at the MS2Discovery Research Institute: Marc Kilgour (Host of the speaker, Tecton 6: Operations Research & Decision Science)
Refreshments will be provided
January 14, 2016
4-5pm | Location: Peters 1017
The MS2Discovery Seminar Series:
Wilfrid Laurier University, 75 University Avenue West, Waterloo
This event is hosted by the MS2Discovery Interdisciplinary Research Institute | Waterloo