A ubiquitous recommender system based on collaborative filtering and social networking data
by Nikolaos Polatidis; Christos K. Georgiadis
International Journal of Intelligent Engineering Informatics (IJIEI), Vol. 3, No. 2/3, 2015

Abstract: The use of mobile devices and the rapid growth of the internet and networking infrastructure has brought the necessity of using ubiquitous recommender systems. However, in mobile devices there are different factors that need to be considered in order to get more useful recommendations and increase the quality of the user experience. This paper gives an overview of the factors related to the quality and proposes a new hybrid recommendation model. The proposed model is based on collaborative filtering and social rating network data. Furthermore, it includes an approach to protect user privacy when context parameters are used, by transferring a subset of the users and ratings in the mobile device and applying the algorithm and context parameters locally. In addition, we recommend the use of classical user-based collaborative filtering, enhanced by the trust network, which is a method that performs better in terms of accuracy when compared with user-based collaborative filtering and trust-aware collaborative filtering. Our approach has been experimentally evaluated and is shown that is both practical and effective.

Online publication date: Mon, 15-Jun-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Engineering Informatics (IJIEI):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com