Spatio-temporal trajectory generating method and device

Abstract

The invention discloses a spatio-temporal trajectory generating method. The method comprises the steps that initial data of a data collection object is acquired; according to the initial data, spatio-temporal trajectory data is generated; the spatio-temporal trajectory data is input to a HBase distributed database cluster; according to query conditions input by a user, collision analysis and / or adjoint analysis is conducted on the spatio-temporal trajectory data in each partition cocurrently to generate a target spatio-temporal trajectory. According to the method, by means of an HBase distributed database technology, analysis can be conducted on the mass data in each partition cocurrently to generate the spatio-temporal trajectory, and then the generation speed and precision of the spatio-temporal trajectory are effectively improved. The invention further discloses a spatio-temporal trajectory generating device which has the advantages as well.

Description

technical field [0001] The present application relates to the field of data mining, in particular to a method and device for generating spatiotemporal trajectories. Background technique [0002] With the rapid development of society, data mining has played a huge role in security, market analysis, etc.; and the mining of space-time trajectory as one of the important branches has a pivotal position. [0003] A spatiotemporal trajectory is a recorded sequence of the position and time of a moving object. Through the analysis of various spatio-temporal trajectory data, the similar and abnormal features in the spatio-temporal trajectory data can be obtained, which in turn helps users find meaningful information from them. For example, analyzing the spatio-temporal trajectories of passengers can provide reasonable strategies for traffic management, and analyzing the spatio-temporal trajectories of people entering and exiting criminal activities can help criminal police investigat...

AI Technical Summary

Problems solved by technology

Since the existing technology uses traditional Oracle database technology to generate spatio-temporal trajectories, the processing speed and capacity are very limited, and therefore it cannot handle massive data well, resulting in low accuracy

In today's era of information explosion, due to the prevalence of the Internet and mobile devices, the amount of data is increasing. Therefore, for massive data, the speed and accuracy of the traditional spatio-temporal trajectory generation method obviously cannot meet the requirements of the times and needs to be improved.

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