A General Multi-Context Embedding Model for Mining Human Trajectory Data.

IEEE Transactions on Knowledge and Data Engineering(2016)

引用 84|浏览135
暂无评分
摘要
The proliferation of location-based social networks, such as Foursquare and Facebook Places, offers a variety of ways to record human mobility, including user generated geo-tagged contents, check-in services, and mobile apps. Although trajectory data is of great value to many applications, it is challenging to analyze and mine trajectory data due to the complex characteristics reflected in human m...
更多
查看译文
关键词
Trajectory,Context,Context modeling,Data models,Distributed databases,Data mining,Mobile communication
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要