Objectives and State-of-the-Art of Location-Based Social Network Recommender Systems

Because of the widespread adoption of GPS-enabled devices, such as smartphones and GPS navigation devices, more and more location information is being collected and available. Compared with traditional ones (e.g., Amazon, Taobao, and Dangdang), recommender systems built on location-based social netw...

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Bibliographic Details
Published in:ACM computing surveys 2019-01, Vol.51 (1), p.1-28
Main Authors: Ding, Zhijun, Li, Xiaolun, Jiang, Changjun, Zhou, Mengchu
Format: Article
Language:English
Subjects:
Computer science
Data mining
Global positioning systems
GPS
Location based services
Navigation
Navigation systems
Preferences
Recommender systems
Satellite navigation systems
Smartphones
Social networks
State of the art
Studies
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Summary:Because of the widespread adoption of GPS-enabled devices, such as smartphones and GPS navigation devices, more and more location information is being collected and available. Compared with traditional ones (e.g., Amazon, Taobao, and Dangdang), recommender systems built on location-based social networks (LBSNs) have received much attention. The former mine users’ preferences through the relationship between users and items, e.g., online commodity, movies and music. The latter add location information as a new dimension to the former, hence resulting in a three-dimensional relationship among users, locations, and activities. In this article, we summarize LBSN recommender systems from the perspective of such a relationship. User, activity, and location are called objects, and recommender objectives are formed and achieved by mining and using such 3D relationships. From the perspective of the 3D relationship among these objects, we summarize the state-of-the-art of LBSN recommender systems to fulfill the related objectives. We finally indicate some future research directions in this area.
ISSN:0360-0300
1557-7341
DOI:10.1145/3154526