Semantics Analytics of Origin-Destination Flows from Crowd Sensed Big Data

• 作者: Abraham Campbell Dongjie Zhu Gengxin Sun Guangsheng Cao Keyong Shen Ning Cao Sheng Bin Shengfang Li Xiuli Han
• 来源期刊: 计算机、材料和连续体(英文)
• 学科: 经济
• 关键词: Origin-destination(OD)flows SEMANTICS ANALYTICS COMPLEX network BIG data analysis
• 年，卷（期）: 2019,（7）
• 页码范围: 227-241
• 页数: 15页
• 分类号: F42

摘要

Monitoring,understanding and predicting Origin-destination(OD)flows in a city is an important problem for city planning and human activity.Taxi-GPS traces,acted as one kind of typical crowd sensed data,it can be used to mine the semantics of OD flows.In this paper,we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China.The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows.Then based on a novel complex network model,a semantics mining method of OD flows is proposed through compounding Points of Interests(POI)network and public transport network to the OD flows network.The propose method would offer a novel way to predict the location characteristic and future traffic conditions accurately.