Discovering Event Regions Using a Large-Scale Trajectory Dataset

• 作者: Ling Yang Shouxu Jiang Zhijun Li
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: BIG data principal component analysis TOPICAL model FLUCTUATION location EVENT region
• 年，卷（期）: 2015,（1）
• 页码范围: 59-60
• 页数: 2页
• 分类号: C5

摘要

The city is facing the unprecedented pressure with the rapid development and the moving population. Some hidden knowledge can be found to service the social with human trajectory data. In this paper, we define a state-ofthe-art concept on fluctuant locations with PCA method and discover the same attribute of fluctuant locations called event with topic model. In the time slice, locations with the same attribute are called event region. Event regions aim to understand the relationship between spatial-temporal locations in the city and to early-warning analyze for the city planning, construction, intelligent navigation, route planning and location based service. We use GeoLife public data to experiment and verify this paper.