Name
Abstract | ||
|---|---|---|
In this paper, we propose a model to operationalise serendipity in content-based recommender systems. The model, called SIRUP, is inspired by the Silvia's curiosity theory, based on the fundamental theory of Berlyne, aims at (1) measuring the novelty of an item with respect to the user profile, and (2) assessing whether the user is able to manage such level of novelty (coping potential). The novelty of items is calculated with cosine similarities between items, using Linked Open Data paths. The coping potential of users is estimated by measuring the diversity of the items in the user profile. We deployed and evaluated the SIRUP model in a use case with TV recommender using BBC programs dataset. Results show that the SIRUP model allows us to identify serendipitous recommendations, and, at the same time, to have 71% precision. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3025171.3025185 | IUI |
Keywords | Field | DocType |
Personalization, Television/Video, Entertainment, Design Methods, Qualitative Methods, User and Cognitive models, User Studies, Serendipity, Recommender System, Curiosity | Recommender system,Curiosity,User profile,Computer science,Linked data,Design methods,Human–computer interaction,Novelty,Multimedia,Personalization,Serendipity | Conference |
Citations | PageRank | References |
2 | 0.39 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| valentina maccatrozzo | 1 | 15 | 3.24 |
| Manon Terstall | 2 | 2 | 0.39 |
| lora aroyo | 3 | 34 | 2.32 |
| Guus Schreiber | 4 | 1448 | 150.58 |