Mobile recommender systems: Identifying the major concepts

Pimenidis, Elias; Polatidis, Nikolaos; Mouratidis, Haralambos

Abstract

© The Author(s) 2018. This article identifies the factors that have an impact on mobile recommender systems. Recommender systems have become a technology that has been widely used by various online applications in situations where there is an information overload problem. Numerous applications such as e-Commerce, video platforms and social networks provide personalised recommendations to their users and this has improved the user experience and vendor revenues. The development of recommender systems has been focused mostly on the proposal of new algorithms that provide more accurate recommendations. However, the use of mobile devices and the rapid growth of the Internet and networking infrastructure have brought the necessity of using mobile recommender systems. The links between web and mobile recommender systems are described along with how the recommendations in mobile environments can be improved. This work is focused on identifying the links between web and mobile recommender systems and to provide solid future directions that aim to lead in a more integrated mobile recommendation domain.

• Journal Article Type: Article
• Acceptance Date: Jul 6, 2018
• Online Publication Date: Aug 3, 2018
• Publication Date: Jun 1, 2019
• Deposit Date: Jul 30, 2018
• Publicly Available Date: Jul 30, 2018
• Journal: Journal of Information Science
• Print ISSN: 0165-5515
• Electronic ISSN: 1741-6485
• Publisher: SAGE Publications
• Peer Reviewed: Peer Reviewed
• Volume: 45
• Issue: 3
• Pages: 387-397
• DOI: https://doi.org/10.1177/0165551518792213
• Keywords: mobile recommender systems, collaborative filtering, context, privacy
• Public URL: https://uwe-repository.worktribe.com/output/864761
• Publisher URL: https://doi.org/10.1177/0165551518792213
• Additional Information: Additional Information : Copyright(c)2018 Reprinted by permission of SAGE publications.
• Contract Date: Jul 30, 2018