%0 Conference Proceedings
%T Recommendation of Learning Objects Applying Collaborative Filtering and Competencies
%+ Universidade do Vale do Rio dos Sinos (UNISINOS)
%+ Universidade Federal do Rio Grande do Sul [Porto Alegre] (UFRGS)
%A Cazella, Sílvio César
%A Reategui, Eliseo Berni
%A Behar, Patrícia
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B IFIP TC 3 International Conference on Key Competencies in the Knowledge Society (KCKS) / Held as Part of World Computer Congress (WCC)
%C Brisbane, Australia
%Y Nicholas Reynolds; Márta Turcsányi-Szabó
%I Springer
%3 Key Competencies in the Knowledge Society
%V AICT-324
%P 35-43
%8 2010-09-20
%D 2010
%R 10.1007/978-3-642-15378-5_4
%K Recommender Systems
%K Collaborative Filtering
%K Competencies
%Z Computer Science [cs]/Digital Libraries [cs.DL]Conference papers
%X This paper presents a recommender system for learning objects which uses a collaborative filtering mechanism based on competencies. The model enables students to receive recommendations of learning objects automatically, according to students' interests but also according to competencies that have to be developed. The prototype implemented was able to recommend relevant contents to students, aiming at helping them in the development of competencies. The paper also presents a couple of experiments showing that the recommender system has a good level of accuracy for the suggestions made.
%G English
%2 https://inria.hal.science/hal-01054676/document
%2 https://inria.hal.science/hal-01054676/file/cazella-KCKS.pdf
%L hal-01054676
%U https://inria.hal.science/hal-01054676
%~ IFIP
%~ IFIP-AICT
%~ IFIP-AICT-324
%~ IFIP-TC
%~ IFIP-TC3
%~ IFIP-WCC
%~ IFIP-2010
%~ IFIP-KCKS