Search

Your search keyword '"Pirlot Marc"' showing total 6 results
Start Over Author "Pirlot Marc" Topic preference learning
6 results on '"Pirlot Marc"'

4. Learning monotone preferences using a majority rule sorting model.

Author

Sobrie, Olivier, Mousseau, Vincent, and Pirlot, Marc

Subjects
LEARNING modules, MONOTONE operators, PROBLEM solving, MULTIPLE criteria decision making, HEURISTIC algorithms
Abstract

We consider the problem of learning a function assigning objects into ordered categories. The objects are described by a vector of attribute values and the assignment function is monotone w.r.t. the attribute values (monotone sorting problem). Our approach is based on a model used in multicriteria decision analysis (MCDA), called MR‐Sort. This model determines the assigned class on the basis of a majority rule and an artificial object that is a typical lower profile of the category. MR‐Sort is a simplified variant of the ELECTRE TRI method. We describe an algorithm designed for learning such a model on the basis of assignment examples. We compare its performance with choquistic regression, a method recently proposed in the preference learning community, and with UTADIS, another MCDA method leaning on an additive value function (utility) model. Our experimentation shows that MR‐Sort competes with the other two methods, and leads to a model that is interpretable. [ABSTRACT FROM AUTHOR]

Published
2019
Full Text
View/download PDF

5. New methodological perspectives on PROMETHEE methods

Author

Van Assche, Dimitri, De Smet, Yves, Birattari, Mauro, Calders, Toon, Decaestecker, Christine, Pirlot, Marc, and Rui Figueira, José

Subjects
promethee, flowsort, Informatique mathématique, preference learning, multicriteria decision aid, Recherche opérationnelle, optimization, clustering
Abstract

A few methodological contributions to the PROMETHEE method, essentially based on 3 articles:-FlowSort parameters elicitation based on categorization examples;-PROMETHEE is Not Quadratic: An O (qnlog (n)) Algorithm;-Lexicographic constrained multicriteria ordered clustering., Doctorat en Sciences de l'ingénieur et technologie, info:eu-repo/semantics/nonPublished

Published
2019

6. Comparative preferences induction methods for conversational recommenders

Author

Walid Trabelsi, Nic Wilson, Derek Bridge, Perny, Patrice, Pirlot, Marc, and Tsoukiàs, Alexis

Subjects
Preference learning, Computer science, Probability and statistics in computer science, Information systems applications (incl. internet), Algorithm analysis and problem complexity, Programming techniques, Preference handling, Recommender system, computer.software_genre, Artificial intelligence (incl. robotics), Preference, Core (game theory), Human–computer interaction, Feature (machine learning), Preference elicitation, Data mining, Computer communication networks, computer, User feedback
Abstract

In an era of overwhelming choices, recommender systems aim at recommending the most suitable items to the user. Preference handling is one of the core issues in the design of recommender systems and so it is important for them to catch and model the user's preferences as accurately as possible. In previous work, comparative preferences-based patterns were developed to handle preferences deduced by the system. These patterns assume there are only two values for each feature. However, real-world features can be multi-valued. In this paper, we develop preference induction methods which aim at capturing several preference nuances from the user feedback when features have more than two values. We prove the efficiency of the proposed methods through an experimental study.

Published
2013

Catalog

Books, media, physical & digital resources
See catalog results