Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 2
375-380

Point-of-interest recommendation model based on semantic location and regional division

Liu Hui1a,1b,2
Wan Chengfeng1a,1b
Wu Xiaohao1a,1b
1. a. College of Communication & Information Engineering, b. Research Center of New Telecommunication Technology Applications, Chongqing University of Posts & Telecommunications, Chongqing 400065, China
2. Chongqing Information Technology Designing Co. Ltd. , Chongqing 401121, China
DOI: 10.19734/j.issn.1001-3695.2018.08.0541

Abstract

According to the existing research work of location-based social network was not sufficient to mine the user semantic location information related to point-of-interest, moreover, most recommendation algorithms ignored the influence of the region of point-of-interest on the result of recommendation, this paper proposed a new recommendation model of point-of-interest called USTTGD. Firstly, it adopted the latent Dirichlet allocation(LDA) topic model of time division, and mined the user time preference under the time theme based on the semantic location information in check-in records. Then it divided the region of point-of-interest into grids to evaluate the regional influence. Next, it applied edge-weighted personalized PageRank(EwPPR) to model the successive transitions among point-of-interests. Finally, USTTGD model fused user time preference, regional preference and successive transition preference into a unified recommendation framework. Experimental results on real-world datasets show that USTTGD model achieves significantly enhance compared with other classical recommendation models on precision and recalling rates.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.08.0541
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 2
Section: Algorithm Research & Explore
Pages: 375-380
Serial Number: 1001-3695(2020)02-012-0375-06

Publish History

[2020-02-05] Printed Article

Cite This Article

刘辉, 万程峰, 吴晓浩. 基于语义位置和区域划分的兴趣点推荐模型 [J]. 计算机应用研究, 2020, 37 (2): 375-380. (Liu Hui, Wan Chengfeng, Wu Xiaohao. Point-of-interest recommendation model based on semantic location and regional division [J]. Application Research of Computers, 2020, 37 (2): 375-380. )

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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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