IRMay 6, 2018

Mobile recommender systems: Identifying the major concepts

arXiv:1805.02276v122 citations
Originality Synthesis-oriented
AI Analysis

It addresses the need for mobile recommender systems due to increased mobile device usage, but is incremental as it focuses on identifying concepts rather than proposing new methods.

This paper identifies factors impacting mobile recommender systems, describing links between web and mobile systems and providing future directions for a more integrated domain.

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.

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