Journal
ARTIFICIAL INTELLIGENCE REVIEW
Volume 44, Issue 4, Pages 571-604Publisher
SPRINGER
DOI: 10.1007/s10462-015-9440-z
Keywords
Recommender systems; e-Learning; Personalization; Collaborative tagging
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Funding
- Ministry of Education, Science and Technological Development of Serbia [174023]
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With the development of sophisticated e-learning environments, personalization is becoming an important feature in e-learning systems due to the differences in background, goals, capabilities and personalities of the large numbers of learners. Personalization can achieve using different type of recommendation techniques. This paper presents an overview of the most important requirements and challenges for designing a recommender system in e-learning environments. The aim of this paper is to present the various limitations of the current generation of recommendation techniques and possible extensions with model for tagging activities and tag-based recommender systems, which can apply to e-learning environments in order to provide better recommendation capabilities.
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