Disseminating Authorized Content via Data Analysis in Opportunistic Social Networks
Authorized content is a type of content that can be generated only by a certain Content Provider (CP). The content copies delivered to a user may bring rewards to the CP if the content is adopted by the user. The overall reward obtained by the CP depends on the user’s degree of interest in the conte...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2019-03-01
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| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2018.9020028 |
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| _version_ | 1832573606592249856 |
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| author | Chenguang Kong Guangchun Luo Ling Tian Xiaojun Cao |
| author_facet | Chenguang Kong Guangchun Luo Ling Tian Xiaojun Cao |
| author_sort | Chenguang Kong |
| collection | DOAJ |
| description | Authorized content is a type of content that can be generated only by a certain Content Provider (CP). The content copies delivered to a user may bring rewards to the CP if the content is adopted by the user. The overall reward obtained by the CP depends on the user’s degree of interest in the content and the user’s role in disseminating the content copies. Thus, to maximize the reward, the content provider is motivated to disseminate the authorized content to the most interested users. In this paper, we study how to effectively disseminate the authorized content in Interest-centric Opportunistic Social Networks (IOSNs) such that the reward is maximized. We first derive Social Connection Pattern (SCP) data to handle the challenging opportunistic connections in IOSNs and statistically analyze the interest distribution of the users contacted or connected. The SCP is used to predict the interests of possible contactors and connectors. Then, we propose our SCP-based Dissemination (SCPD) algorithm to calculate the optimum number of content copies to disseminate when two users meet. Our dataset based simulation shows that our SCPD algorithm is effective and efficient to disseminate the authorized content in IOSNs. |
| format | Article |
| id | doaj-art-2563564e3f8d43d083652db6c8890469 |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2019-03-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-2563564e3f8d43d083652db6c88904692025-02-02T03:44:40ZengTsinghua University PressBig Data Mining and Analytics2096-06542019-03-0121122410.26599/BDMA.2018.9020028Disseminating Authorized Content via Data Analysis in Opportunistic Social NetworksChenguang Kong0Guangchun Luo1Ling Tian2Xiaojun Cao3<institution content-type="dept">Department of Computer Science</institution>, <institution>Georgia State University</institution>, <city>Atlanta</city>, <state>GA</state> <postal-code>30309</postal-code>, <country>USA</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>University of Electronic Science and Technology of China</institution>, <city>Chengdu</city> <postal-code>610054</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>University of Electronic Science and Technology of China</institution>, <city>Chengdu</city> <postal-code>610054</postal-code>, <country>China</country>.<institution content-type="dept">Department of Computer Science</institution>, <institution>Georgia State University</institution>, <city>Atlanta</city>, <state>GA</state> <postal-code>30309</postal-code>, <country>USA</country>.Authorized content is a type of content that can be generated only by a certain Content Provider (CP). The content copies delivered to a user may bring rewards to the CP if the content is adopted by the user. The overall reward obtained by the CP depends on the user’s degree of interest in the content and the user’s role in disseminating the content copies. Thus, to maximize the reward, the content provider is motivated to disseminate the authorized content to the most interested users. In this paper, we study how to effectively disseminate the authorized content in Interest-centric Opportunistic Social Networks (IOSNs) such that the reward is maximized. We first derive Social Connection Pattern (SCP) data to handle the challenging opportunistic connections in IOSNs and statistically analyze the interest distribution of the users contacted or connected. The SCP is used to predict the interests of possible contactors and connectors. Then, we propose our SCP-based Dissemination (SCPD) algorithm to calculate the optimum number of content copies to disseminate when two users meet. Our dataset based simulation shows that our SCPD algorithm is effective and efficient to disseminate the authorized content in IOSNs.https://www.sciopen.com/article/10.26599/BDMA.2018.9020028high-speed train (hst)condition recognitionmulti-view clusteringfuzzy clustering |
| spellingShingle | Chenguang Kong Guangchun Luo Ling Tian Xiaojun Cao Disseminating Authorized Content via Data Analysis in Opportunistic Social Networks Big Data Mining and Analytics high-speed train (hst) condition recognition multi-view clustering fuzzy clustering |
| title | Disseminating Authorized Content via Data Analysis in Opportunistic Social Networks |
| title_full | Disseminating Authorized Content via Data Analysis in Opportunistic Social Networks |
| title_fullStr | Disseminating Authorized Content via Data Analysis in Opportunistic Social Networks |
| title_full_unstemmed | Disseminating Authorized Content via Data Analysis in Opportunistic Social Networks |
| title_short | Disseminating Authorized Content via Data Analysis in Opportunistic Social Networks |
| title_sort | disseminating authorized content via data analysis in opportunistic social networks |
| topic | high-speed train (hst) condition recognition multi-view clustering fuzzy clustering |
| url | https://www.sciopen.com/article/10.26599/BDMA.2018.9020028 |
| work_keys_str_mv | AT chenguangkong disseminatingauthorizedcontentviadataanalysisinopportunisticsocialnetworks AT guangchunluo disseminatingauthorizedcontentviadataanalysisinopportunisticsocialnetworks AT lingtian disseminatingauthorizedcontentviadataanalysisinopportunisticsocialnetworks AT xiaojuncao disseminatingauthorizedcontentviadataanalysisinopportunisticsocialnetworks |