Collaborative filtering adapted to recommender systems of e-learning

@article{Bobadilla2009CollaborativeFA,
  title={Collaborative filtering adapted to recommender systems of e-learning},
  author={Jes{\'u}s Bobadilla and Francisco Serradilla and Antonio Hernando},
  journal={Knowl.-Based Syst.},
  year={2009},
  volume={22},
  pages={261-265}
}
In the context of e-learning recommender systems, we propose that the users with greater knowledge (for example, those who have obtained better results in various tests) have greater weight in the calculation of the recommendations than the users with less knowledge. To achieve this objective, we have designed some new equations in the nucleus of the memory-based collaborative filtering, in such a way that the existent equations are extended to collect and process the information relative to… CONTINUE READING
Highly Cited
This paper has 159 citations. REVIEW CITATIONS

From This Paper

Topics from this paper.
84 Citations
0 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 84 extracted citations

159 Citations

0102030'10'12'14'16'18
Citations per Year
Semantic Scholar estimates that this publication has 159 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…