Content Recommendation Algorithm for Intelligent Navigator in Fog Computing Based IoT Environment
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lin, Fuhong | - |
dc.contributor.author | Zhou, Yutong | - |
dc.contributor.author | You, Ilsun | - |
dc.contributor.author | Lin, Jiuzhi | - |
dc.contributor.author | An, Xingshuo | - |
dc.contributor.author | Lu, Xing | - |
dc.date.accessioned | 2021-08-11T11:23:41Z | - |
dc.date.available | 2021-08-11T11:23:41Z | - |
dc.date.issued | 2019 | - |
dc.identifier.issn | 2169-3536 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/5336 | - |
dc.description.abstract | With the development of the Internet and mobile technologies, the Internet of Things (IoT) era has arrived. Vehicle networking technology can not only facilitate people's travel but also effectively alleviate traffic congestion. The development of fog computing technology provides unlimited possibilities for the Internet of Vehicles (IoV). Intelligent navigator is a very important part of human-computer interaction in IoV. It carries a large number of tasks of recommending content for users. In order to get more accurate recommendation content, we propose a weighted interest degree recommendation algorithm using association rules for intelligence in the IoV. First, the user data are analyzed to establish the association rule mining algorithm. Second, the user interest score is predicted by analyzing the relevance between user interests to recommend personalized service for the user. From the simulation results, we can see that the proposed algorithm can achieve higher recommendation accuracy. | - |
dc.format.extent | 10 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Content Recommendation Algorithm for Intelligent Navigator in Fog Computing Based IoT Environment | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1109/ACCESS.2019.2912897 | - |
dc.identifier.scopusid | 2-s2.0-85065404185 | - |
dc.identifier.wosid | 000467032800001 | - |
dc.identifier.bibliographicCitation | IEEE Access, v.7, pp 53677 - 53686 | - |
dc.citation.title | IEEE Access | - |
dc.citation.volume | 7 | - |
dc.citation.startPage | 53677 | - |
dc.citation.endPage | 53686 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | NETWORKS | - |
dc.subject.keywordAuthor | Content recommendation | - |
dc.subject.keywordAuthor | association rules | - |
dc.subject.keywordAuthor | Internet of Vehicles | - |
dc.subject.keywordAuthor | fog computing | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(31538) 22, Soonchunhyang-ro, Asan-si, Chungcheongnam-do, Republic of Korea+82-41-530-1114
COPYRIGHT 2021 by SOONCHUNHYANG UNIVERSITY ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.