PMID- 35427385
OWN - NLM
STAT- MEDLINE
DCOM- 20220419
LR  - 20231103
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 17
IP  - 4
DP  - 2022
TI  - Relational POI recommendation model combined with geographic information.
PG  - e0266340
LID - 10.1371/journal.pone.0266340 [doi]
LID - e0266340
AB  - Point of interest (POI) recommendation is a popular personalized location-based 
      service. This paper proposes a Geographic Personal Matrix Factorization (GPMF) 
      model that makes effective use of geographic information from the perspective of 
      the relationship between POIs and users. This model considers the role of 
      geographic information from multiple perspectives based on the locational 
      relationship among users, the distributional relationship between users and POIs, 
      and the proximity and clustering relationship among POIs. The GPMF mines the 
      influence of geographic information on different objects and carries out unique 
      modeling through cosine similarity, non-linear function, and k nearest neighbor 
      (KNN). This study explored the influence of geographic information on POI 
      recommendation through extensive experiments with data from Foursquare. The 
      result shows that GPMF performs better than the commonly used POI recommendation 
      algorithm in terms of both precision and recall. Geographic information through 
      proximity relations effectively improves the recommendation algorithm.
FAU - Li, Ke
AU  - Li K
AD  - The School of the Geo-Science & Technology, Zhengzhou University, Zhengzhou, 
      Henan, China.
AD  - Joint Laboratory of Eco-Meteorology, Zhengzhou University, Chinese Academy of 
      Meteorological Sciences, Zhengzhou, Henan, China.
FAU - Wei, Haitao
AU  - Wei H
AD  - The School of the Geo-Science & Technology, Zhengzhou University, Zhengzhou, 
      Henan, China.
AD  - Joint Laboratory of Eco-Meteorology, Zhengzhou University, Chinese Academy of 
      Meteorological Sciences, Zhengzhou, Henan, China.
FAU - He, Xiaohui
AU  - He X
AD  - The School of the Geo-Science & Technology, Zhengzhou University, Zhengzhou, 
      Henan, China.
AD  - Joint Laboratory of Eco-Meteorology, Zhengzhou University, Chinese Academy of 
      Meteorological Sciences, Zhengzhou, Henan, China.
FAU - Tian, Zhihui
AU  - Tian Z
AD  - The School of the Geo-Science & Technology, Zhengzhou University, Zhengzhou, 
      Henan, China.
AD  - Joint Laboratory of Eco-Meteorology, Zhengzhou University, Chinese Academy of 
      Meteorological Sciences, Zhengzhou, Henan, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20220415
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
SB  - IM
MH  - *Algorithms
MH  - Cluster Analysis
MH  - Female
MH  - Humans
MH  - *Primary Ovarian Insufficiency
MH  - Serogroup
PMC - PMC9012400
COIS- The authors have declared that no competing interests exist.
EDAT- 2022/04/16 06:00
MHDA- 2022/04/20 06:00
PMCR- 2022/04/15
CRDT- 2022/04/15 17:09
PHST- 2021/06/02 00:00 [received]
PHST- 2022/03/21 00:00 [accepted]
PHST- 2022/04/15 17:09 [entrez]
PHST- 2022/04/16 06:00 [pubmed]
PHST- 2022/04/20 06:00 [medline]
PHST- 2022/04/15 00:00 [pmc-release]
AID - PONE-D-21-17914 [pii]
AID - 10.1371/journal.pone.0266340 [doi]
PST - epublish
SO  - PLoS One. 2022 Apr 15;17(4):e0266340. doi: 10.1371/journal.pone.0266340. 
      eCollection 2022.