%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 }