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Reseach Article

Socially-Aware Recommender Systems

by Nana Yaw Asabere, Wisdom Kwawu Torgby, Tonny Montana Adegboyega, Dorothy Anima Frempong
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 3
Year of Publication: 2015
Authors: Nana Yaw Asabere, Wisdom Kwawu Torgby, Tonny Montana Adegboyega, Dorothy Anima Frempong
10.5120/20134-2224

Nana Yaw Asabere, Wisdom Kwawu Torgby, Tonny Montana Adegboyega, Dorothy Anima Frempong . Socially-Aware Recommender Systems. International Journal of Computer Applications. 115, 3 ( April 2015), 34-38. DOI=10.5120/20134-2224

@article{ 10.5120/20134-2224,
author = { Nana Yaw Asabere, Wisdom Kwawu Torgby, Tonny Montana Adegboyega, Dorothy Anima Frempong },
title = { Socially-Aware Recommender Systems },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 3 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number3/20134-2224/ },
doi = { 10.5120/20134-2224 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:53:47.139552+05:30
%A Nana Yaw Asabere
%A Wisdom Kwawu Torgby
%A Tonny Montana Adegboyega
%A Dorothy Anima Frempong
%T Socially-Aware Recommender Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 3
%P 34-38
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In current social networks, users are characterized by social properties. Are these social properties relevant in a recommendation process? Can social properties such as social ties and degree centrality of users be applied to generate effective recommendations? In answering these questions, the authors draw pertinent literature and argue that indeed the incorporation of social properties in recommender systems is very significant for generating reliable recommendations for users. The authors envisage that innovative research in recommender systems should integrate the social properties of users in order to generate trustworthy and efficient recommendations.

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Index Terms

Computer Science
Information Sciences

Keywords

Mobile Social Networks Online Social Networks Recommender Systems Social Properties.