Recommendation system of learning object through collaborative filtering
DOI:
https://doi.org/10.25044/25392190.824Keywords:
Similarity metric, Learning object, User profile, Recommendation system, Collaborative filtering.Abstract
Learning objects collaborative filtering recommender systems support students in their autonomous learning process, by finding resources that liked, interest or served a student with similar characteristics. These systems are based on the concept that if two people to be similar and one likes an item, there is a high probability that the other person also likes that item, meaning item as any material available (documents, videos, images, resources, among others). Therefore, in this paper a model is presented recommendation by collaborative filtering, where to find the similarity between users a combination of several metrics that measure this value, with the aim of finding a greater amount of similar users used. Tests were performed to a case study and the results show that the use of collaborative recommendation system delivers relevant and pertinent learning objects for students.Downloads
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