Location-based clustering and collaborative filtering for mobile learning
by Mohammad M. Alnabhan
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 19, No. 1, 2018

Abstract: This paper presents a new m-learning model described as location-based collaborative M-learning (LCM). This new model exploits location information of mobile users and implements two main operations; k-means for clustering mobile users, and location-based collaborative filtering (CF) to provide learning items recommendations to clustered users. A comprehensive evaluation methodology was utilised to validate the proposed model in terms of complexity, performance and learning items' recommendations quality. Results have confirmed successful implementation of the proposed LCM model during different mobile users' settings. It was shown that LCM structure efficiently reduces processing overload and time required for users' clustering and learning content authoring, and improves learning items recommendations' accuracy.

Online publication date: Thu, 09-Aug-2018

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 Networking and Virtual Organisations (IJNVO):
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