兴趣点推荐方法研究综述

doi:10.11896/jsjkx.201100021

Abstract

Abstract: Point-of-interest (POI) recommendation is an important service in location-based social networks (LBSN),which has an important impact on both merchants and customers.As a typical example of spatio-temporal data,POI recommendation has been widely concerned,so it has become a hot research topic in academic circles in recent years.This paper analyzes the influencing factors of interest point recommendation,summarizes the traditional methods of interest point recommendation,the latest graph-based embedding methods and the application of graph neural networks in the field of point-of-interest recommendation are analyzed.Finally,it analyzes the challenges faced by points of interest recommendation and future research trends.

Key words: Graph embedding method, Graph neural network, Influencing factors, Point-of-interest recommendation

CLC Number:

TP301

XING Chang-zheng, ZHU Jin-xia, MENG Xiang-fu, QI Xue-yue, ZHU Yao, ZHANG Feng, YANG Yi-ming. Point-of-interest Recommendation:A Survey[J].Computer Science, 2021, 48(11A): 176-183.

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