Journal of Frontiers of Computer Science and Technology ›› 2022, Vol. 16 ›› Issue (7): 1462-1478.DOI: 10.3778/j.issn.1673-9418.2112037

• Surveys and Frontiers • Previous Articles     Next Articles

Review of Point of Interest Recommendation Systems in Location-Based Social Networks

CHEN Jiangmei1, ZHANG Wende2,+()   

  1. 1. School of Economy and Management, Fuzhou University, Fuzhou 350108, China
    2. Institute of Information Management, Fuzhou University, Fuzhou 350108, China
  • Received:2021-12-09 Revised:2022-02-14 Online:2022-07-01 Published:2022-07-25
  • Supported by:
    the National Natural Science Foundation for Youth of China(61300104);the New Generation Information Technology Innovation Project of Industry-University-Research Innovation Fund in Chinese Universities(2019ITA0103)


陈江美1, 张文德2,+()   

  1. 1.福州大学 经济与管理学院,福州 350108
    2.福州大学 信息管理研究所,福州 350108
  • 作者简介:陈江美(1995—),女,福建南平人,博士研究生,主要研究方向为商务智能、数据挖掘等。
    CHEN Jiangmei, born in 1995, Ph.D. candidate. Her research interests include business intelligence, data mining, etc.
    ZHANG Wende, born in 1962, Ph.D., professor. His research interests include information management, intellectual property, etc.
  • 基金资助:


Point of interest recommendation is recently one of the hotspots in the field of location-based social networks and recommendation systems. Understanding the research status of the point of interest recommendation in location-based social networks can provide a direction for the next step of work. The recent literatures of the point of interest recommendation systems are analyzed. Firstly, the definition is introduced, and the difference from traditional recommendation is discussed from three aspects: influencing factors, recommendation approaches and existing problems. Secondly, the general framework of the point of interest recommendation is proposed, which includes data sources, recommendation approaches and evaluation. Based on this framework, the various influencing factors are introduced, the current recommendation algorithms are generalized, and the evaluation metrics are summarized. Meanwhile, the representative works are analyzed, the research contents and characteristics of each type of methods are summarized in detail, and their advantages and limitations are evaluated. Finally, the challenges and potential directions for possible extensions in this filed are summarized and prospected, and the future research trends and development directions are concluded.

Key words: location-based social networks, recommendation systems, point of interest recommendation, influencing factor



关键词: 位置社交网络, 推荐系统, 兴趣点推荐, 影响因素

CLC Number: