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Ricci, F., Rokach, L., Shapira, B. and Kantor, P.B. (2011) Introduction to Recommender Systems Handbook. In: Ricci, F., Rokach, L., Shapira, B. and Kantor, P.B., Eds., Recommender Systems Handbook, Springer, Berlin, 1-35.
http://dx.doi.org/10.1007/978-0-387-85820-3_1

has been cited by the following article:

• TITLE: A Survey of Online Course Recommendation Techniques

  AUTHORS: Jinliang Lu

  KEYWORDS: Information Overload, Recommender Systems, Personalization, Online Course

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.12 No.1, January 25, 2022

  ABSTRACT: With the development of information technology, online learning has gradually become an indispensable way of knowledge acquisition. However, with the increasing amount of data information, it is increasingly difficult for people to find appropriate learning materials from a large number of educational resources. The recommender system has been widely used in various Internet applications due to its high efficiency in filtering information, helping users to quickly find personalized resources from thousands of information, thereby alleviating the problem of information overload. In addition, due to its great use value, many new researches have been proposed in the field of recommender systems in recent years, but there are not many works on online course recommendation at present. Therefore, this paper aims to sort out the existing cutting-edge recommendation algorithms and the work related to online course recommendation, so as to provide a comprehensive overview of the online course recommender system. Specifically, we will first introduce the main technologies and representative work used in the online course recommender system, explain the advantages and disadvantages of various technologies, and finally discuss the future research direction of the online course recommender system.