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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.1
- 수록면
- 123 - 133 (11page)
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초록· 키워드
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With the popularization of social network and global positioning technology, location-based social network applications have developed rapidly. Location-based social network data contains a lot of interest information. In order to solve the problem of poor recommendation result caused by the strong sparsity of matrix in traditional recommendation algorithm. This paper proposes a method of interest point recommendation based on location classification and user similarity. Social regularization is used to constrain the difference of location category preference in social relations, which solves the data sparsity problem of collaborative filtering. The proposed algorithm was tested using Foursquare public dataset and compared with the relevant algorithm. Experimental results show that the proposed algorithm has high precision and recall.
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등록된 정보가 없습니다.
참고문헌 (15)
참고문헌 신청
Jinying Jia / 2015 / Non-deterministic k-anonymity algorithm based untrusted third party for location privacy protection in LBS / International Journal of Security and Its Applications 9(9):387~400
Minho Cho / 2018 / Response analysis model of social networks using fuzzy sets and system dynamics / International Journal of Grid and Distributed Computing 11(4):1~12
Zhao Z / 2019 / Mutual graph embedding in lbsn: capturing multi-factor influence for point-of-interest prediction / 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced &Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation
Ye M / 2011 / Exploiting geographical influence for collaborative point-of-interest recommendation / Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval :325~334
Yuan Q / 2013 / Time-aware point-of-interest recommendation / Proceedings of the 36th international ACMSIGIR conference on Research and development in information retrieval :363~372
Minho Cho / 2018 / Response analysis model of social networks using fuzzy sets and system dynamics / International Journal of Grid and Distributed Computing 11(4):1~12
Zhao Z / 2019 / Mutual graph embedding in lbsn: capturing multi-factor influence for point-of-interest prediction / 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced &Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation
Ye M / 2011 / Exploiting geographical influence for collaborative point-of-interest recommendation / Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval :325~334
Yuan Q / 2013 / Time-aware point-of-interest recommendation / Proceedings of the 36th international ACMSIGIR conference on Research and development in information retrieval :363~372
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