Name
Abstract | ||
|---|---|---|
•Ads social recommenders challenged by sparsity, cold-start and heterogeneity.•Semantic Web technologies enable data integration and support recommendation.•Shared ontology model aligns advertisements with users’ profiles.•Textual contributions and network connections leveraged to improve recommendation.•Accuracy boosted adapting user profiles to changing needs. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ipm.2019.102153 | Information Processing & Management |
Keywords | DocType | Volume |
Knowledge-based systems,Recommender systems,Natural language processing,Advertising,Social network services | Journal | 57 |
Issue | ISSN | Citations |
2 | 0306-4573 | 4 |
PageRank | References | Authors |
0.43 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francisco García-Sánchez | 1 | 402 | 22.62 |
| Ricardo Colomo-Palacios | 2 | 614 | 67.78 |
| Rafael Valencia-Garcia | 3 | 36 | 5.61 |