Name
Abstract | ||
|---|---|---|
This paper presents a Generalist Recommender System Kernel (GRSK) and describes the differences of the recommendation process when it is applied to groups. The GRSK is able to work with any domain as long as the domain description is represented within an ontology. Several basic techniques like demographics, content-based or collaborative are used to elicit the recommendations, as well as other hybrid techniques. The GRSK provides a configuration process through which to select the techniques and parameters that best suit the particular application domain. The experiments will show the success of the GRSK in different domains. We also outline the changes and new techniques required by the GRSK when it is used in a group recommendation. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-22810-0_16 | Lecture Notes in Business Information Processing |
Keywords | Field | DocType |
Recommender systems,Group recommenders,Tourism,Movies | Kernel (linear algebra),Recommender system,Ontology,World Wide Web,Computer science,Tourism,Generalist and specialist species,Application domain,Demographics | Conference |
Volume | ISSN | Citations |
75 | 1865-1348 | 0 |
PageRank | References | Authors |
0.34 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Inma Garcia | 1 | 146 | 6.56 |
| L. Sebastia | 2 | 296 | 24.12 |
| Sergio Pajares | 3 | 43 | 2.65 |
| Eva Onaindia | 4 | 534 | 55.65 |