Name
Abstract | ||
|---|---|---|
A good movie is like a good book. As a good book can serve entertaining and learning purposes, so does a movie. In addition to that, movies are in general more engaging and reach a wider audience. In this work, we present and evaluate a method that overcomes the challenge of generating recommendations among heterogeneous resources. In our case, we recommend movies in the context of a learning object. We evaluate our method with 60 participants that judged the relevance of the recommendations. Results show that, in over 74% of the cases the recommendations are in fact related to the given learning object, outperforming a text-based recommendation approach. The implications of our work can take learning outside the classroom and invoke it during the joy of watching a movie. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICALT.2013.53 | ICALT |
Keywords | Field | DocType |
computer aided instruction,recommender systems,content-based movie recommendation,heterogeneous resources,learning contexts,learning object | Recommender system,Computer aided instruction,World Wide Web,Computer science,Learning object,Multimedia | Conference |
ISSN | Citations | PageRank |
2161-3761 | 3 | 0.40 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ricardo Kawase | 1 | 100 | 9.99 |
| Bernardo Pereira Nunes | 2 | 185 | 30.96 |
| Patrick Siehndel | 3 | 126 | 15.69 |