User Recommendation for Data Sharing in Social Internet of Things
As various types of data are generated on the social Internet of things (SIoT), which combine the Internet of things (IoT) and social networks, the relations of IoT devices should be established for necessary data exchange. In this paper, we propose a user recommendation scheme that facilitates data...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-01-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/2/462 |
| _version_ | 1797413268804861952 |
|---|---|
| author | Kyoungsoo Bok Yeondong Kim Dojin Choi Jaesoo Yoo |
| author_facet | Kyoungsoo Bok Yeondong Kim Dojin Choi Jaesoo Yoo |
| author_sort | Kyoungsoo Bok |
| collection | DOAJ |
| description | As various types of data are generated on the social Internet of things (SIoT), which combine the Internet of things (IoT) and social networks, the relations of IoT devices should be established for necessary data exchange. In this paper, we propose a user recommendation scheme that facilitates data sharing through an analysis of an interaction between an IoT device and a user in the SIoT. An interrelation between a user and an IoT device as well as an interrelation between users exist simultaneously in the SIoT. Hence, the interaction between users must be analyzed to identify the interest keywords, and the interaction between IoT devices and users to determine the user’s preference of IoT device. Moreover, the proposed scheme calculates the similarity between users based on the IoT device preference based on IoT device usage frequency and interest keywords, which are identified through an analysis between the user and IoT device and that between users. Subsequently, it recommends top-N users who have a high similarity as the users for data sharing. Furthermore, the performance of the proposed scheme is verified through performance evaluation based on the precision, recall, and F-measure. |
| first_indexed | 2024-03-09T05:15:29Z |
| format | Article |
| id | doaj.art-e5bfb314ff3e498fba4ef599dfc571c5 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T05:15:29Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e5bfb314ff3e498fba4ef599dfc571c52023-12-03T12:46:09ZengMDPI AGSensors1424-82202021-01-0121246210.3390/s21020462User Recommendation for Data Sharing in Social Internet of ThingsKyoungsoo Bok0Yeondong Kim1Dojin Choi2Jaesoo Yoo3Department of SW Convergence Technology, Wonkwang University, Iksandae 460, Iksan, Jeonbuk 54538, KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, KoreaAs various types of data are generated on the social Internet of things (SIoT), which combine the Internet of things (IoT) and social networks, the relations of IoT devices should be established for necessary data exchange. In this paper, we propose a user recommendation scheme that facilitates data sharing through an analysis of an interaction between an IoT device and a user in the SIoT. An interrelation between a user and an IoT device as well as an interrelation between users exist simultaneously in the SIoT. Hence, the interaction between users must be analyzed to identify the interest keywords, and the interaction between IoT devices and users to determine the user’s preference of IoT device. Moreover, the proposed scheme calculates the similarity between users based on the IoT device preference based on IoT device usage frequency and interest keywords, which are identified through an analysis between the user and IoT device and that between users. Subsequently, it recommends top-N users who have a high similarity as the users for data sharing. Furthermore, the performance of the proposed scheme is verified through performance evaluation based on the precision, recall, and F-measure.https://www.mdpi.com/1424-8220/21/2/462social internet of thingsdata sharinginteraction analysissimilarityuser recommendation |
| spellingShingle | Kyoungsoo Bok Yeondong Kim Dojin Choi Jaesoo Yoo User Recommendation for Data Sharing in Social Internet of Things Sensors social internet of things data sharing interaction analysis similarity user recommendation |
| title | User Recommendation for Data Sharing in Social Internet of Things |
| title_full | User Recommendation for Data Sharing in Social Internet of Things |
| title_fullStr | User Recommendation for Data Sharing in Social Internet of Things |
| title_full_unstemmed | User Recommendation for Data Sharing in Social Internet of Things |
| title_short | User Recommendation for Data Sharing in Social Internet of Things |
| title_sort | user recommendation for data sharing in social internet of things |
| topic | social internet of things data sharing interaction analysis similarity user recommendation |
| url | https://www.mdpi.com/1424-8220/21/2/462 |
| work_keys_str_mv | AT kyoungsoobok userrecommendationfordatasharinginsocialinternetofthings AT yeondongkim userrecommendationfordatasharinginsocialinternetofthings AT dojinchoi userrecommendationfordatasharinginsocialinternetofthings AT jaesooyoo userrecommendationfordatasharinginsocialinternetofthings |