Name
Abstract | ||
|---|---|---|
One of the unresolved issues when designing a recommender system is the number of ratings -- i.e., the profile length -- that should be collected from a new user before providing recommendations. A design tension exists, induced by two conflicting requirements. On the one hand, the system must collect "enough"ratings from the user in order to learn her/his preferences and improve the accuracy of recommendations. On the other hand, gathering more ratings adds a burden on the user, which may negatively affect the user experience. Our research investigates the effects of profile length from both a subjective (user-centric) point of view and an objective (accuracy-based) perspective. We carried on an offline simulation with three algorithms, and a set of online experiments involving overall 960 users and four recommender algorithms, to measure which of the two contrasting forces influenced by the number of collected ratings -- recommendations relevance and burden of the rating process -- has stronger effects on the perceived quality of the user experience. Moreover, our study identifies the potentially optimal profile length for an explicit, rating based, and human controlled elicitation strategy. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2365952.2365963 | RecSys |
Keywords | Field | DocType |
recommendations relevance,recommender algorithm,rating-based elicitation,conflicting requirement,rating process,recommender system,user experience,optimal profile length,new user,design tension,user effort,profile length,elicitation,accuracy,negative affect | Recommender system,Data mining,User experience design,Computer science | Conference |
Citations | PageRank | References |
21 | 0.97 | 24 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paolo Cremonesi | 1 | 1306 | 87.23 |
| Franca Garzottto | 2 | 21 | 0.97 |
| Roberto Turrin | 3 | 859 | 34.94 |