Recent Developments in Recommender Systems


Low, Jia Ming and Tan, Ian Kim Teck and Ting, Choo Yee (2019) Recent Developments in Recommender Systems. Lecture Notes in Computer Science, 11909. pp. 38-51. ISSN 0302-9743

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With greater penetration of online services, the use of recommender systems to predict users’ propensity for continuous engagement becomes crucial in ensuring maximum revenue. There are many challenges, such as the cold start problem and data sparsity, that are continuously being addressed by a myriad of techniques in recommender systems. This paper provides insights into the trends of the techniques used for recommender systems and the challenges they address. With the insights; deep learning, matrix factorization or a combination of both can be used in addressing the data sparsity challenge.

Item Type: Article
Uncontrolled Keywords: Recommender Systems, Recommender systems (Information filtering)
Subjects: Z Bibliography. Library Science. Information Resources > ZA3038-5190 Information resources (General)
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 14 Sep 2021 00:39
Last Modified: 14 Sep 2021 00:39


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