Journal of Jilin University(Engineering and Technology Edition) ›› 2019, Vol. 49 ›› Issue (5): 1653-1660.doi: 10.13229/j.cnki.jdxbgxb20181264

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Location recommendation algorithm based on K-means and matrix factorization

Bin LI1(),Xu ZHOU2(),Fang MEI3,Shuai-ning PAN4   

  1. 1. College of Mathematics, Jilin University, Changchun 130012, China
    2. Center for Computer Fundamental Education, Jilin University, Changchun 130012, China
    3. College of Computer Science and Technology, Jilin University, Changchun 130012, China
    4. College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
  • Received:2018-12-22 Online:2019-09-01 Published:2019-09-11
  • Contact: Xu ZHOU E-mail:lb@jlu.edu.cn;zhoux16@jlu.edu.cn

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Abstract:

In this paper, a novel POI recommendation algorithm based on clustering and matric factorization is proposed. The matrix factorization method is used to quantify the user's number of check-in for unknown location. The clustering method is used to divide the users into groups. In addition, the improved similarity calculation method is used to calculate the similarity among users. The experiment results on Yelp dataset show that the proposed method can improve the location recommendation recall rate and accuracy rate, demonstrating the better performance of our method compared to other methods.

Key words: computer application, matrix factorization, K-means clustering, location recommendation, location based social network

CLC Number: 

  • TP391.3

Fig.1

Location based social network"

Fig.2

Comparative precision obtained by CF and FCF"

Fig.3

Comparative recall obtained by CF and FCF"

Fig.4

Comparative F value obtained by CF and FCF"

Fig.5

Precision value obtained by KMF with different K "

Fig.6

Recall value obtained by KMF with different K "

Fig.7

F value obtained by KMF with different K "

Fig.8

Comparative precision obtained by three algorithms"

Fig.9

Comparative recall obtained by three algorithms"

Fig.10

Comparative F obtained by three algorithms"

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