Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
Popular social networks sites such as Facebook and Twitter are still growing significantly. In this regard, a recommender system can be used to provide user experiences. In this study, we try modeling the online communities using naive bayes model. More specifically, the core of this work is modeling the user’s past friends by taking into account the centrality measures and the latest friends. The two real datasets Facebook-Ego and Twitter are consider as a test bed for our proposed system then precision and recall measures have been applied to evaluate the accuracy of the system. In addition, a new metric, namely the Rtop-list metric is suggested to express the accuracy of prediction. In sum, the empirical results foster the efficiency of the proposed system.
How to cite this article:
Huda N. Nawaf, Wafaa. Al-Hameed and Najah Rasheed Jouda. Friend Recommendation System based on Modeling the
Communities using Naive Bayes.
DOI: https://doi.org/10.36478/jeasci.2017.4156.4160
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2017.4156.4160