A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes
The existing approaches to predict trust values in social commerce are based on personal social relationships without considering historical transaction information about products in social commerce, which results in false recommendations, and deceptions cannot be differentiated. Trust values extrac...
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Series: | Security and Communication Networks |
Online Access: | http://dx.doi.org/10.1155/2020/8887596 |
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doaj-e37906c25dae4402ad89319daea5a3de2020-11-25T04:11:34ZengHindawi-WileySecurity and Communication Networks1939-01141939-01222020-01-01202010.1155/2020/88875968887596A Comprehensive Trust Model Based on Social Relationship and Transaction AttributesYonghua Gong0Lei Chen1Tinghuai Ma2School of Management, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaSchool of Management, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaNanjing University of Information Science & Technology, Nanjing 210044, ChinaThe existing approaches to predict trust values in social commerce are based on personal social relationships without considering historical transaction information about products in social commerce, which results in false recommendations, and deceptions cannot be differentiated. Trust values extracted from social links can improve the performance of trust and reputation mechanism, but the rates from these links in social commerce can be false because of the stakeholders’ manipulation for personal interest. And the rates are also dynamic and inconsistent. Therefore, this paper proposes a comprehensive trust model by fully exploiting the effects of the transaction attributes and social relationships on users’ trust. The proposed model refines the granularity of trust evaluation and improves the discrimination of recommended information. Experiments demonstrate that the proposed model performs better and predicts more accurately than the three models compared under the same circumstance.http://dx.doi.org/10.1155/2020/8887596 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yonghua Gong Lei Chen Tinghuai Ma |
spellingShingle |
Yonghua Gong Lei Chen Tinghuai Ma A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes Security and Communication Networks |
author_facet |
Yonghua Gong Lei Chen Tinghuai Ma |
author_sort |
Yonghua Gong |
title |
A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes |
title_short |
A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes |
title_full |
A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes |
title_fullStr |
A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes |
title_full_unstemmed |
A Comprehensive Trust Model Based on Social Relationship and Transaction Attributes |
title_sort |
comprehensive trust model based on social relationship and transaction attributes |
publisher |
Hindawi-Wiley |
series |
Security and Communication Networks |
issn |
1939-0114 1939-0122 |
publishDate |
2020-01-01 |
description |
The existing approaches to predict trust values in social commerce are based on personal social relationships without considering historical transaction information about products in social commerce, which results in false recommendations, and deceptions cannot be differentiated. Trust values extracted from social links can improve the performance of trust and reputation mechanism, but the rates from these links in social commerce can be false because of the stakeholders’ manipulation for personal interest. And the rates are also dynamic and inconsistent. Therefore, this paper proposes a comprehensive trust model by fully exploiting the effects of the transaction attributes and social relationships on users’ trust. The proposed model refines the granularity of trust evaluation and improves the discrimination of recommended information. Experiments demonstrate that the proposed model performs better and predicts more accurately than the three models compared under the same circumstance. |
url |
http://dx.doi.org/10.1155/2020/8887596 |
work_keys_str_mv |
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