Group Recommender Systems Based on Members’ Preference for Trusted Social Networks
Joint Authors
Wang, Xiangshi
Su, Lei
Zhou, Qihang
Wu, Liping
Source
Security and Communication Networks
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-19
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
With the development of the Internet of Things (IoT), the group recommender system has also been extended to the field of IoT.
The entities in the IoT are linked through social networks, which constitute massive amounts of data.
In group activities such as group purchases and group tours, user groups often exhibit common interests and hobbies, and it is necessary to make recommendations for certain user groups.
This idea constitutes the group recommender system.
However, group members’ preferences are not fully considered in group recommendations, and how to use trusted social networks based on their preferences remains unclear.
The focus of this paper is group recommendation based on an average strategy, where group members have preferential differences and use trusted social networks to correct for their preferences.
Thus, the accuracy of the group recommender system in the IoT and big data environment is improved.
American Psychological Association (APA)
Wang, Xiangshi& Su, Lei& Zhou, Qihang& Wu, Liping. 2020. Group Recommender Systems Based on Members’ Preference for Trusted Social Networks. Security and Communication Networks،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1208363
Modern Language Association (MLA)
Wang, Xiangshi…[et al.]. Group Recommender Systems Based on Members’ Preference for Trusted Social Networks. Security and Communication Networks No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1208363
American Medical Association (AMA)
Wang, Xiangshi& Su, Lei& Zhou, Qihang& Wu, Liping. Group Recommender Systems Based on Members’ Preference for Trusted Social Networks. Security and Communication Networks. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1208363
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208363