Social Trust-Aware Recommendation System: A T-Index Approach
A. Zarghami, S. Fazeli, N. Dokoohaki, and M. Matskin. Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03, page 85--90. Washington, DC, USA, IEEE Computer Society, (2009)
DOI: 10.1109/WI-IAT.2009.237
Abstract
Collaborative Filtering based on similarity suffers from a variety of problems such as sparsity and scalability. In this paper, we propose an ontological model of trust between users on a social network to address the limitations of similarity measure in Collaborative Filtering algorithms. For enhancing the constructed network of users based on trust, we introduce an estimate of a user’s trustworthiness called T-index to identify and select neighbors in an effective manner. We employ T-index to store raters of an item in a so-called TopTrustee list which provides information about users who might not be accessible within a predefined maximum path length. An empirical evaluation shows that our solution improves both prediction accuracy and coverage of recommendations collected along few edges that connect users on a social network by exploiting T-index. We also analyze effect of T-index on structure of trust network to justify the results.
%0 Conference Paper
%1 zarghami2009social
%A Zarghami, Alireza
%A Fazeli, Soude
%A Dokoohaki, Nima
%A Matskin, Mihhail
%B Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
%C Washington, DC, USA
%D 2009
%I IEEE Computer Society
%K recommendation social system trust
%P 85--90
%R 10.1109/WI-IAT.2009.237
%T Social Trust-Aware Recommendation System: A T-Index Approach
%U http://dx.doi.org/10.1109/WI-IAT.2009.237
%X Collaborative Filtering based on similarity suffers from a variety of problems such as sparsity and scalability. In this paper, we propose an ontological model of trust between users on a social network to address the limitations of similarity measure in Collaborative Filtering algorithms. For enhancing the constructed network of users based on trust, we introduce an estimate of a user’s trustworthiness called T-index to identify and select neighbors in an effective manner. We employ T-index to store raters of an item in a so-called TopTrustee list which provides information about users who might not be accessible within a predefined maximum path length. An empirical evaluation shows that our solution improves both prediction accuracy and coverage of recommendations collected along few edges that connect users on a social network by exploiting T-index. We also analyze effect of T-index on structure of trust network to justify the results.
%@ 978-0-7695-3801-3
@inproceedings{zarghami2009social,
abstract = {Collaborative Filtering based on similarity suffers from a variety of problems such as sparsity and scalability. In this paper, we propose an ontological model of trust between users on a social network to address the limitations of similarity measure in Collaborative Filtering algorithms. For enhancing the constructed network of users based on trust, we introduce an estimate of a user’s trustworthiness called T-index to identify and select neighbors in an effective manner. We employ T-index to store raters of an item in a so-called TopTrustee list which provides information about users who might not be accessible within a predefined maximum path length. An empirical evaluation shows that our solution improves both prediction accuracy and coverage of recommendations collected along few edges that connect users on a social network by exploiting T-index. We also analyze effect of T-index on structure of trust network to justify the results.},
acmid = {1632250},
added-at = {2012-10-10T11:25:46.000+0200},
address = {Washington, DC, USA},
author = {Zarghami, Alireza and Fazeli, Soude and Dokoohaki, Nima and Matskin, Mihhail},
biburl = {https://www.bibsonomy.org/bibtex/24fd983d5d6ccc7a09eb608530b2ff067/nimdoc},
booktitle = {Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03},
doi = {10.1109/WI-IAT.2009.237},
interhash = {e21c335823f5a998e42ccfb90e3acd77},
intrahash = {4fd983d5d6ccc7a09eb608530b2ff067},
isbn = {978-0-7695-3801-3},
keywords = {recommendation social system trust},
numpages = {6},
pages = {85--90},
publisher = {IEEE Computer Society},
series = {WI-IAT '09},
timestamp = {2012-10-10T11:25:46.000+0200},
title = {Social Trust-Aware Recommendation System: A T-Index Approach},
url = {http://dx.doi.org/10.1109/WI-IAT.2009.237},
year = 2009
}