This paper 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 personalized 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 has 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||Journal of Information Science|
|Publication status||Published - 3 Aug 2018|
Bibliographical noteElias Pimenidis, Nikolaos Polatidis & Haralambos Mouratidis, Mobile Recommender Systems: Identifying the major concepts, Journal of Information Science 2018. Copyright © 2018. Reprinted by permission of SAGE Publications.
- Mobile recommender systems
- Collaborative filtering
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