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• W2775285377 abstract "Adapting an educational environment to students considering its features and individuals is a necessity due to the large amount of learning objects in the repositories. Thus, organizing learning objects so that they can be efficiently recommended is a real need. In this way, this work presents a proposal for clustering learning objects in repositories considering the learning styles they support, in order to facilitate the content recommendation process based on students' learning styles. For this, a comparative analysis of clustering techniques was performed, and the most efficient was used in the implementation of this approach. Experiments were conducted and promising results were obtained." @default.
• W2775285377 created "2017-12-22" @default.
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• W2775285377 date "2017-10-01" @default.
• W2775285377 modified "2023-09-27" @default.
• W2775285377 title "Clustering learning objects in the IEEE-LOM standard considering learning styles to support customized recommendation systems in educational environments" @default.
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• W2775285377 doi "https://doi.org/10.1109/laclo.2017.8120898" @default.
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