A Survey of Point-of-interest recommendation in Location-based Social Networks

PhD Qualifying Examination


Title: "A Survey of Point-of-interest recommendation in Location-based 
Social Networks"

by

Mr. Guanyao LI


Abstract:

Point-of-interest (POI) refers to a place that people may find useful or 
interesting. POI recommendation aims to recommend POIs to users, which the 
users may be interested in and visit in the future. In recent years, POI 
recommendation has attracted much attention in both industry and academia 
due to its commercial and social value. POI recommendation is a 
challenging problem because of the data-sparse problem and the implicit 
feedback problem. Besides, whether a user would visit a POI is affected by 
various influence, such as geographical influences, social influence, 
temporal influence, etc. To provide an efficient POI recommendation, 
multiple types of information have been exploited to model users' 
preferences and to address the challenges of POI recommendation in the 
existing works.

In this survey, we offer a systematic review of the research about POI 
recommendation, presenting some representative works, and providing a 
comparison between related works. We categorize the existing works based 
on how to exploit different types of information to tackle the challenges 
for POI recommendation. We mainly introduce two groups of works, the pure 
models and the hybrid models. In the group of the pure models, we discuss 
works about modeling pure information, including geographical information, 
temporal information, social information, sequential information, and POI 
content information. In the group of the hybrid models, we present some 
hybrid models which fuse different information for POI recommendation. For 
each group of works, we introduce some representative works, presenting 
the intuitions, and highlighting the contributions of the works. 
Furthermore, to illustrate the relation of the works, we provide 
comparisons of the existing works within each category.  Our survey can 
serve as an educating study for new researchers in the field of POI 
recommendation.


Date:			Wednesday, 28 August 2019

Time:                  	10:00am - 12:00noon

Venue:                  Room 3494
                         Lifts 25/26

Committee Members:	Prof. Gary Chan (Supervisor)
 			Dr. Qiong Luo (Chairperson)
 			Dr. Kai Chen
 			Prof. Ke Yi


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