Journal of Information Science · 2018 · 27 citations · 28 references
ComputingComputer ScienceInformation SystemsMobile ComputingMobile SystemsRecommender SystemsCollaborative FilteringMobile CommerceMobile Human-computer InteractionMobile User ExperienceRecommendation SystemsInformation OverloadInformation Overload ManagementMobile Recommendation SystemsNetworkingPersonalization In Mobile Systems
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.
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A Survey of Collaborative Filtering Techniques
Xiaoyuan Su, Taghi M. Khoshgoftaar · Advances in Artificial Intelligence · 2009 · 3.6K citations · Full text
Jesús Bobadilla, Fernando Ortega, Antonio Hernando et al. · Knowledge-Based Systems · 2013 · 3.1K citations
Recommender system application developments: A survey
Jie Lü, Dianshuang Wu, Mingsong Mao et al. · Decision Support Systems · 2015 · 1.6K citations