Social Networks have dominated growth and popularity of the Web to an extent which has never been witnessed before. Such popularity puts forward issue of trust to the participants of Social Networks. Collaborative Filtering Recommenders have been among many systems which have begun taking full advantage of Social Trust phenomena for generating more accurate predictions. For analyzing the evolution of constructed networks of trust, we utilize Collaborative Filtering enhanced with T-index as an estimate of a user’s trustworthiness to identify and select neighbors in an effective manner. Our empirical evaluation demonstrates how T-index improves the Trust Network structure by generating connections to more trustworthy users. We also show that exploiting T-index results in better prediction accuracy and coverage of recommendations collected along few edges that connect users on a network.
%0 Book Section
%1 fazeli2010mechanizing
%A Fazeli, Soude
%A Zarghami, Alireza
%A Dokoohaki, Nima
%A Matskin, Mihhail
%B Trust, Privacy and Security in Digital Business
%C Berlin / Heidelberg
%D 2010
%E Katsikas, Sokratis
%E Lopez, Javier
%E Soriano, Miguel
%I Springer
%K algorithm design recommender social system trust
%P 202-213
%R 10.1007/978-3-642-15152-1_18
%T Mechanizing Social Trust-Aware Recommenders with T-Index Augmented Trustworthiness
%U http://dx.doi.org/10.1007/978-3-642-15152-1_18
%V 6264
%X Social Networks have dominated growth and popularity of the Web to an extent which has never been witnessed before. Such popularity puts forward issue of trust to the participants of Social Networks. Collaborative Filtering Recommenders have been among many systems which have begun taking full advantage of Social Trust phenomena for generating more accurate predictions. For analyzing the evolution of constructed networks of trust, we utilize Collaborative Filtering enhanced with T-index as an estimate of a user’s trustworthiness to identify and select neighbors in an effective manner. Our empirical evaluation demonstrates how T-index improves the Trust Network structure by generating connections to more trustworthy users. We also show that exploiting T-index results in better prediction accuracy and coverage of recommendations collected along few edges that connect users on a network.
%@ 978-3-642-15151-4
@incollection{fazeli2010mechanizing,
abstract = {Social Networks have dominated growth and popularity of the Web to an extent which has never been witnessed before. Such popularity puts forward issue of trust to the participants of Social Networks. Collaborative Filtering Recommenders have been among many systems which have begun taking full advantage of Social Trust phenomena for generating more accurate predictions. For analyzing the evolution of constructed networks of trust, we utilize Collaborative Filtering enhanced with T-index as an estimate of a user’s trustworthiness to identify and select neighbors in an effective manner. Our empirical evaluation demonstrates how T-index improves the Trust Network structure by generating connections to more trustworthy users. We also show that exploiting T-index results in better prediction accuracy and coverage of recommendations collected along few edges that connect users on a network.},
added-at = {2012-10-10T11:30:41.000+0200},
address = {Berlin / Heidelberg},
affiliation = {Royal Institute of Technology (KTH)},
author = {Fazeli, Soude and Zarghami, Alireza and Dokoohaki, Nima and Matskin, Mihhail},
biburl = {https://www.bibsonomy.org/bibtex/2ce4df9ba5ca0a2558df84b95dc7d42a4/nimdoc},
booktitle = {Trust, Privacy and Security in Digital Business},
doi = {10.1007/978-3-642-15152-1_18},
editor = {Katsikas, Sokratis and Lopez, Javier and Soriano, Miguel},
interhash = {bda71fd9f51d7f499945493013803abe},
intrahash = {ce4df9ba5ca0a2558df84b95dc7d42a4},
isbn = {978-3-642-15151-4},
keyword = {Computer Science},
keywords = {algorithm design recommender social system trust},
pages = {202-213},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
timestamp = {2012-10-10T11:30:41.000+0200},
title = {Mechanizing Social Trust-Aware Recommenders with T-Index Augmented Trustworthiness},
url = {http://dx.doi.org/10.1007/978-3-642-15152-1_18},
volume = 6264,
year = 2010
}