Name
Abstract | ||
|---|---|---|
Nowadays, e-learning systems are widely used for education and training in universities and companies because of their electronic course content access and virtual classroom participation. However, with the rapid increase of learning content on the Web, it will be time-consuming for learners to find contents they really want to and need to study. Aiming at enhancing the efficiency and effectiveness of learning, we propose an ontology-based approach for semantic content recommendation towards context-aware e-learning. The recommender takes knowledge about the learner (user context), knowledge about content, and knowledge about the domain being learned into consideration. Ontology is utilized to model and represent such kinds of knowledge. The recommendation consists of four steps: semantic relevance calculation, recommendation refining, learning path generation, and recommendation augmentation. As a result, a personalized, complete, and augmented learning program is suggested for the learner. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-73549-6_88 | UIC |
Keywords | Field | DocType |
semantic content recommendation,recommendation refining,ontology-based approach,ontology-based semantic recommendation,semantic relevance calculation,rapid increase,context-aware e-learning,recommendation augmentation,e-learning system,electronic course content access,path generation | Augmented learning,Ontology,World Wide Web,E learning,Computer science,Virtual classroom,Path generation,Semantic relevance,Multimedia | Conference |
Volume | ISSN | ISBN |
4611 | 0302-9743 | 3-540-73548-8 |
Citations | PageRank | References |
35 | 1.55 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiwen Yu | 1 | 2753 | 220.67 |
| Yuichi Nakamura | 2 | 93 | 15.10 |
| Seiie Jang | 3 | 92 | 7.41 |
| Shoji Kajita | 4 | 147 | 21.92 |
| Kenji Mase | 5 | 1066 | 308.34 |