Mobile recommender systems: Identifying the major concepts

Haralambos Mouratidis,Elias Pimenidis,Nikolaos Polatidis

doi:10.1177/0165551518792213

Haralambos Mouratidis, Elias Pimenidis + Show 1 more

Open Access

https://doi.org/10.1177/0165551518792213

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Abstract

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.

Highlights

Recommender systems research is becoming increasingly important in e-Commerce environments
Mobile recommender systems are based on a recommendation algorithm and contextual information to provide recommendations of items or services to users of mobile devices
In (Lathia, 2015) an overview of mobile recommender systems is given with the outcome that a mobile recommendation domain does not exist and that every mobile recommender system is developed with a specific task in mind

Summary

Introduction

Recommender systems research is becoming increasingly important in e-Commerce environments. In (Lathia, 2015) an overview of mobile recommender systems is given with the outcome that a mobile recommendation domain does not exist and that every mobile recommender system is developed with a specific task in mind This argument is present in other works in the literature such as An important problem identified it as the lack of a good quality datasets for the purpose and the research is based on specific mobile domains These include the development of mobile recommender systems for the recommendations of generic commerce items like books, movies, music and photos or the recommendations of points of interest (POIs) such as restaurants and tourist attractions. The remaining part of this chapter concentrates on the coverage of related works found both in the general commerce and in the tourism domains respectively

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