Method of spatiotemporal-frequent-region mining based on multi-dimensional time granularities

A technology of time granularity and space-time, which is applied in marketing, instruments, satellite radio beacon positioning systems, etc., can solve the problems of low advertising efficiency, insufficient semantic information mining, and failure to achieve expected results, so as to improve the efficiency of advertising Effect

Active Publication Date: 2018-06-29
NORTHWEST UNIV
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AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a method for mining frequent spatio-temporal regions based on multi-dimensional time granularity, so as to solve the problem of insufficient mining of semantic information of movi

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  • Method of spatiotemporal-frequent-region mining based on multi-dimensional time granularities
  • Method of spatiotemporal-frequent-region mining based on multi-dimensional time granularities
  • Method of spatiotemporal-frequent-region mining based on multi-dimensional time granularities

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Embodiment Construction

[0041] Comply with the above technical solutions, such as Figure 1 to Figure 10 As shown, the present invention discloses a method for mining frequent space-time regions based on multi-dimensional time granularity, comprising the following steps:

[0042] Step 1, collecting the location information of the moving object and the corresponding time information;

[0043] The mobile object mentioned in this solution refers to a mobile device capable of sending and receiving GPS data, and generally refers to a pedestrian carrying a mobile device. The mobile device here can be a mobile phone, a computer, and other devices with built-in GPS modules.

[0044] Specifically, in this embodiment, the location information is a GPS movement track, the GPS track data includes longitude and latitude, and the time information refers to the time corresponding to each piece of GPS track data.

[0045] This program studies the moving objects within a fixed map range. In this application, the mov...

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Abstract

The invention discloses a method of spatiotemporal-frequent-region mining based on multi-dimensional time granularities. The method includes: collecting location information of a moving object and corresponding time information; dividing a time period of interest according to a time granularity hierarchy to form the multi-layer time granularities; acquiring spatiotemporal staying regions of the moving object under all the time granularities according to the location information; calculating spatiotemporal frequent regions of the moving object under all the time granularities according to the acquired spatiotemporal staying regions; calculating core spatiotemporal-frequent-regions of the moving object under all the time granularities according to the spatiotemporal frequent regions; and acquiring activity rules of the moving object according to information of the core spatiotemporal-frequent-regions, and formulating an advertising strategy based on the location information. The method is used for solving the problem of spatiotemporal-frequent-region moving-object activity-law semantic-information mining insufficiency under single time granularities and scenes of location-based advertising, and improves advertising efficiency.

Description

technical field [0001] The invention relates to a method for mining frequent space-time regions, in particular to a method for mining frequent space-time regions based on multi-dimensional time granularity. Background technique [0002] With the development of mobile communication and positioning technology, a large amount of trajectory data is collected from various mobile devices, and the analysis and mining research based on trajectory data has attracted the attention of domain experts and the industry. Trajectory data records the activity rules of mobile objects in the real world. By analyzing the historical trajectories of mobile objects, the geographical areas frequently visited by mobile objects are found, and valuable information is provided for location-based services, such as traffic flow control and location-based travel recommendations. , Advertisement recommendations, location selection for shared bicycles, etc. [0003] The current research studies from the as...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G01S19/42
CPCG01S19/42G06Q30/0261
Inventor 冯宏伟马佳丽高原王东冯筠
Owner NORTHWEST UNIV
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