Name
Abstract | ||
|---|---|---|
Social systems by their definition encourage interaction between users and both on-line content and other users thus generating new sources of knowledge that is valuable for recommender systems. In this paper we deal with the situation of having a recommender system where, even if a social structure implicitly exist, its users are not explicitly connected through a social network. We describe SocialFan, a domain independent tool that allows defining and integrating the social network infrastructure to capture and use the social knowledge into an existing recommender system. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICTAI.2018.00035 | 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) |
Keywords | Field | DocType |
Recommender systems,Social Network,Influence | Recommender system,Data science,Social network,Social knowledge,Computer science,Artificial intelligence,Social system,Knowledge engineering,Machine learning | Conference |
ISSN | ISBN | Citations |
1082-3409 | 978-1-5386-7450-5 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Belén Díaz-agudo | 1 | 484 | 49.71 |
| Guillermo Jiménez-díaz | 2 | 56 | 8.56 |
| Juan A. Recio-garcía | 3 | 185 | 14.75 |