A fundamental task for reasoning with preferences is the following: given input preference information from a user, and outcomes α and β, should we infer that the user will prefer α to β? For CP-nets and related comparative preference formalisms, inferring a preference of α over β using the standard definition of derived preference appears to be extremely hard, and has been proved to be PSPACEc...

Many real-world applications are characterized by a number of conflicting performance measures. As optimizing in a multi-objective setting leads to a set of non-dominated solutions, a preference function is required for selecting the solution with the appropriate trade-off between the objectives. This preference function is often unknown, especially when it comes from an expert human user. Howe...

Complex application domains like outdoor activity platforms demand a powerful search interface that can adapt to personal user preferences and to changing contexts like weather conditions. Today most platforms offer a search technology known as Faceted Search, also named Parametric Search, where a user iteratively adapts his/her search parameters by a tedious and time-consuming trial-and-error ...

Collaborative filtering has been successfully applied for predicting a person’s preference on an item, by aggregating community preference on the item. Typically, collaborative filtering systems are based on based on quantitative preference modeling, which requires users to express their preferences in absolute numerical ratings. However, quantitative user ratings are known to be biased and inc...

This chapter reports the project MARS (Multiplicative Adaptive Refinement Search), which applies a new multiplicative adaptive algorithm for user preference retrieval to Web search. The new algorithm uses a multiplicative query expansion strategy to adaptively improve and reformulate the query vector to learn users’ information preference. The algorithm has provable better performance than the ...

A fundamental task for reasoning with preferences is the following: given input preference information from a user, and outcomes α and β, should we infer that the user will prefer α to β? For CP-nets and related comparative preference formalisms, inferring a preference of α over β using the standard definition of derived preference appears to be extremely hard, and has been proved to be PSPACEc...

The success of a music recommendation (MR) system heavily relies on its ability to identify user needs. Existing approaches, including collaborative filtering and contentbased methods, overlook the fact that user needs is inherently subjective and largely time-variant. In this work, we propose an interactive MR system (iMR) to tackle these issues. A user is asked to provide his/her preference f...

It is of key importance that all representations used in the software development process can be clearly understood by all who must use them. User preference is one area that may influence the effectiveness of the representations presented. Described in this paper is a study that was carried out to explore the relationship between user preference for UML sequence and collaboration diagrams. Ana...