Preference elicitation plays a central role in interactive recommender systems. Most
preference elicitation approaches use either item queries that ask users to select preferred …

Effective techniques for eliciting user preferences have taken on added importance as
recommender systems (RSs) become increasingly interactive and conversational. A …

This paper deals with preference elicitation within Choquet Expected Utility (CEU) theory for
decision making under uncertainty. We consider the Savage's framework with a finite set of …

Multi-Criteria Decision Making (MCDM) aims at modelling expert preferences and assisting
decision makers in identifying options best accommodating expert criteria. An instance of …

Identifying the preferences of a given user through elicitation is a central part of multi-criteria
decision aid (MCDA) or preference learning tasks. Two classical ways to perform this …

Abstract The Simple Ranking Method using Reference Profiles (or SRMP) is a Multi-Criteria
Decision Aiding technique based on the outranking paradigm, which allows to rank decision …

In this paper, we address the issues of gathering the preferences of a user when they may
be uncertain, and of handling the possible ensuing inconsistency. We suggest using …

In a decision-making problem, there is often some uncertainty regarding the user
preferences. We assume a parameterised utility model, where in each scenario we have a …

This study introduces a fund recommendation system based on the ϵ-greedy algorithm and
an incremental learning framework. This model simulates the interaction process when …

The development of models that can cope with noisy input preferences is a critical topic in
artificial intelligence methods for interactive preference elicitation. A Bayesian …