Name
Abstract | ||
|---|---|---|
This paper presents a solution for recommending documents to students according to their current activity that is tracked in terms of semantic annotations associated to the accessed resources. Our approach is based on an existing tracking system that captures the user current activity, which is extended to build a user profile that comprises his/her interests in term of ontological concepts. A recommendation service is elaborated, implementing an algorithm that is alimented by Contextualized Attention Metadata (CAM) comprising the annotation of documents accessed by learners. The user profile is updated as soon as an activity is completed; thus, recommendations provided by the service are up-to-date in real time. The original aspect of this recommendation approach consists in combining a user activity tracking system with the exploitation of the semantic annotations associated with resources. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.procs.2010.08.009 | Procedia Computer Science |
Keywords | Field | DocType |
Personalized recommendation,Attention metadata,semantic web,Annotation-based algorithm,Ontology-based modeling | Ontology,Metadata,Data mining,World Wide Web,User profile,Annotation,Information retrieval,Computer science,Semantic Web,Tracking system,Activity tracking | Journal |
Volume | Issue | ISSN |
1 | 2 | 1877-0509 |
Citations | PageRank | References |
7 | 0.54 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julien Broisin | 1 | 65 | 14.80 |
| Mihaela Brut | 2 | 49 | 9.99 |
| Valentin Butoianu | 3 | 18 | 2.01 |
| Florence Sedes | 4 | 191 | 43.06 |
| Philippe Vidal | 5 | 7 | 0.54 |