UrbanHubble: Location Prediction and Geo-Social Analytics in LBSN

被引：0
|
作者：
Assam, Roland [1 ]
Feiden, Simon [1 ]
Seidl, Thomas [1 ]
机构：
[1] Rhein Westfal TH Aachen, Aachen, Germany
来源：
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT III | 2015年 / 9286卷
关键词：
D O I：
10.1007/978-3-319-23461-8_41
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Massive amounts of geo-social data is generated daily. In this paper, we propose UrbanHubble, a location-based predictive analytics tool that entails a broad range of state-of-the-art location prediction and recommendation algorithms. Besides, UrbanHubble consists of a visualization component that depicts the real-time complex interactions of users on a map, the evolution of friendships over time, and how friendship triggers mobility.
引用
收藏
页码：329 / 332
页数：4
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