Name
Abstract | ||
|---|---|---|
More and more personalization systems are emerging to reduce the information overload of the Web. As a result, it has become vital to model users' preferences accurately. Our focus lies in the quality of users' expressed preferences, in terms of reliability and stability through time. Today, users are often brought to express their preferences through ratings on a multi-point scale. However, several studies have highlighted problems with ratings. We propose a new preference modality whereby users compare items two-by two ("I prefer x to y").This initial work on comparisons shows that users are in favor of this new preference mechanism and that comparisons are almost 20% more stable over time than those conveyed through ratings, thus more reliable. These encouraging findings let us think that comparisons may lead to a better user modeling and an increase in the quality of personalization services, such as recommender systems. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/WI-IAT.2011.13 | WI-IAT), 2011 IEEE/WIC/ACM International Conference |
Keywords | Field | DocType |
Internet,information management,personal information systems,Web information overload,multipoint scale,personalization system,preference mechanism,recommender system,user modeling,user preference,comparisons,personalization,preference expression,ratings,stability | Recommender system,Information management,Information overload,World Wide Web,Computer science,User modeling,Personalization,The Internet | Conference |
Volume | ISBN | Citations |
1 | 978-0-7695-4513-4 | 19 |
PageRank | References | Authors |
0.99 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolas Jones | 1 | 19 | 0.99 |
| Armelle Brun | 2 | 138 | 21.49 |
| Anne Boyer | 3 | 106 | 18.08 |