Critiquing-based recommender systems elicit users' feedback, called critiques, which they
made on the recommended items. This conversational style of interaction is in contract to the …

This editorial of the special issue “Representing, Processing, and Learning Preferences:
Theoretical and Practical Challenges” surveys past and ongoing research on preferences in …

If we assume that an important function of recommender systems is to help people make
better choices, it follows that people who design and study recommender systems ought to …

We present a tutorial introduction to the area of preference handling-one of the core issues
in the design of any system that automates or supports decision making. The main goal of …

We consider interactive tools that help users search for their most preferred item in a large
collection of options. In particular, we examine example-critiquing, a technique for enabling …

Recommender systems need to mirror the complexity of the environment they are applied in.
The more we know about what might benefit the user, the more objectives the recommender …

A critiquing-based recommender system acts like an artificial salesperson. It engages users
in a conversational dialog where users can provide feedback in the form of critiques to the …

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 …

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 …

In this paper we present a two-fold generalization of conditional preference networks (CP-
nets) that incorporates uncertainty. CP-nets are a formal tool to model qualitative conditional …