A Shared Interest Discovery Model for Coauthor Relationship in SNS

A social network service (SNS) is a platform to build social networks or social relations among people. Many users enjoy SNS with their smart devices, which are mostly equipped with sensory devices. The sensitive information produced by these sensory devices is uploaded to SNS, which may raise many...

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Main Authors: Xin An, Shuo Xu, Yali Wen, Mingxing Hu
Format: Article
Language:English
Published: SAGE Publishing 2014-04-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2014/820715
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spelling doaj-86e72b1a754940bbab8024ccc61074502020-11-25T03:27:19ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772014-04-011010.1155/2014/820715820715A Shared Interest Discovery Model for Coauthor Relationship in SNSXin An0Shuo Xu1Yali Wen2Mingxing Hu3 School of Economics and Management, Beijing Forestry University, No. 35 Qinghua East Road, Haidian District, Beijing 100083, China Information Technology Supporting Center, Institute of Scientific and Technical Information of China, No. 15 fuxing Road, Haidian District, Beijing 100038, China School of Economics and Management, Beijing Forestry University, No. 35 Qinghua East Road, Haidian District, Beijing 100083, China School of Economics and Management, Beijing Forestry University, No. 35 Qinghua East Road, Haidian District, Beijing 100083, ChinaA social network service (SNS) is a platform to build social networks or social relations among people. Many users enjoy SNS with their smart devices, which are mostly equipped with sensory devices. The sensitive information produced by these sensory devices is uploaded to SNS, which may raise many potential risks. In order to share one's sensitive data with random people without security and privacy concerns, this paper proposes a shared interest discovery model for coauthor relationship in SNS, named as coauthor topic (coAT) model, to identify the users with similar interests from social networks, and collapsed Gibbs sampling method is utilized for inferring model parameters. Thus, one can reduce the possibility that recommended users are not friends but attackers. Finally, extensive experimental results on NIPS dataset indicate that our coAT model is feasible and efficient.https://doi.org/10.1155/2014/820715
collection DOAJ
language English
format Article
sources DOAJ
author Xin An
Shuo Xu
Yali Wen
Mingxing Hu
spellingShingle Xin An
Shuo Xu
Yali Wen
Mingxing Hu
A Shared Interest Discovery Model for Coauthor Relationship in SNS
International Journal of Distributed Sensor Networks
author_facet Xin An
Shuo Xu
Yali Wen
Mingxing Hu
author_sort Xin An
title A Shared Interest Discovery Model for Coauthor Relationship in SNS
title_short A Shared Interest Discovery Model for Coauthor Relationship in SNS
title_full A Shared Interest Discovery Model for Coauthor Relationship in SNS
title_fullStr A Shared Interest Discovery Model for Coauthor Relationship in SNS
title_full_unstemmed A Shared Interest Discovery Model for Coauthor Relationship in SNS
title_sort shared interest discovery model for coauthor relationship in sns
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2014-04-01
description A social network service (SNS) is a platform to build social networks or social relations among people. Many users enjoy SNS with their smart devices, which are mostly equipped with sensory devices. The sensitive information produced by these sensory devices is uploaded to SNS, which may raise many potential risks. In order to share one's sensitive data with random people without security and privacy concerns, this paper proposes a shared interest discovery model for coauthor relationship in SNS, named as coauthor topic (coAT) model, to identify the users with similar interests from social networks, and collapsed Gibbs sampling method is utilized for inferring model parameters. Thus, one can reduce the possibility that recommended users are not friends but attackers. Finally, extensive experimental results on NIPS dataset indicate that our coAT model is feasible and efficient.
url https://doi.org/10.1155/2014/820715
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AT shuoxu asharedinterestdiscoverymodelforcoauthorrelationshipinsns
AT yaliwen asharedinterestdiscoverymodelforcoauthorrelationshipinsns
AT mingxinghu asharedinterestdiscoverymodelforcoauthorrelationshipinsns
AT xinan sharedinterestdiscoverymodelforcoauthorrelationshipinsns
AT shuoxu sharedinterestdiscoverymodelforcoauthorrelationshipinsns
AT yaliwen sharedinterestdiscoverymodelforcoauthorrelationshipinsns
AT mingxinghu sharedinterestdiscoverymodelforcoauthorrelationshipinsns
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