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Spatio-temporal pattern mining method of mobile trajectory generation model based on multi-source data fusion

A technology of moving trajectory and multi-source data, applied in data mining, electrical digital data processing, special data processing applications, etc., can solve the problems of many artificially defined factors and weak generalization of the method, and achieve the reduction of subjective factors, strong generalization effect

Active Publication Date: 2019-01-08
BEIHANG UNIV
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Problems solved by technology

The disadvantage of the above method is that when building the model, there are many artificially defined factors, and the generalization of the method is not strong

Method used

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  • Spatio-temporal pattern mining method of mobile trajectory generation model based on multi-source data fusion
  • Spatio-temporal pattern mining method of mobile trajectory generation model based on multi-source data fusion
  • Spatio-temporal pattern mining method of mobile trajectory generation model based on multi-source data fusion

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Embodiment Construction

[0035] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0036] The spatio-temporal pattern mining method of the multi-source data fusion movement trajectory generation model provided by the present invention will be described in detail below.

[0037] 1. Data requirements

[0038] Because the moving trajectory data is actually a time series of position data (latitude and longitude), therefore, except the moving trajectory data, other data involved in the present invention include at least a position attribute and a...

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Abstract

The invention discloses a spatio-temporal pattern mining method of a mobile trajectory generation model based on multi-source data fusion. This method introduces multi-source data into mobile trajectory data mining, constructs a mobile trajectory generation model based on probability graph model, and with time-space constraints, mining of spatio-temporal patterns of urban trajectory data under multi-source data is conducted. The method greatly reduces man-defined factors and has strong generalization.

Description

technical field [0001] The invention relates to the technical fields of data mining and smart cities, and more specifically relates to a spatio-temporal pattern mining method of a moving trajectory generation model fused with multi-source data. Background technique [0002] Mobile trajectory pattern mining is currently a research hotspot in the intersection of data mining and smart cities. It uses the movement trajectory data generated in the city, such as cars, people, bicycles, etc. to mine traffic-related patterns existing in urban roads or areas. Its research content involves urban planning, urban functional zoning, traffic mode research, etc. [0003] The research object of the existing urban mobility trajectory pattern mining technology is mostly a kind of trajectory data, such as taxi trajectory data, mobile phone data and bicycle data. Most of these data mining techniques do not involve the fusion of multi-source data, and the patterns they discover can only reflec...

Claims

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Application Information

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IPC IPC(8): G06F16/2458
CPCG06F2216/03
Inventor 王静远陈超吴俊杰熊璋
Owner BEIHANG UNIV
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