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User Classification Method and System Based on Mobile User Trajectory Similarity

A technology of mobile users and classification methods, applied in the field of communication, can solve problems such as the occurrence of sparse matrices, catastrophic execution of data sparsity algorithms, and high computational complexity

Active Publication Date: 2020-06-19
GCI SCI & TECH
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  • Claims
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AI Technical Summary

Problems solved by technology

Since this algorithm needs to establish a matrix for the base stations and users of the whole city, this will inevitably lead to the appearance of a sparse matrix, and the sparsity of data will bring disastrous consequences to the execution of the algorithm.
Traditional mobile user trajectory similarity calculation methods have the disadvantage of high computational complexity

Method used

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  • User Classification Method and System Based on Mobile User Trajectory Similarity
  • User Classification Method and System Based on Mobile User Trajectory Similarity
  • User Classification Method and System Based on Mobile User Trajectory Similarity

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Embodiment Construction

[0023] In one embodiment, a user classification method based on the similarity of mobile user trajectories, such as figure 1 shown, including the following steps:

[0024] Step S110: receiving and extracting the mobile track data of the mobile users to obtain the time and position information of each mobile user.

[0025] The mobile trajectory data specifically includes the starting time of the mobile user's business, the name of the starting base station, the time of switching the base station, the name of the switching base station, the length of stay in each base station, the calling number, the called number, and the type of business that the user occurred and other data. The trajectory of a mobile user generally consists of a series of locations sorted by time, Tr i ={(L 1 , t 1 ), (L 2 , t 2 ),…, (L i , t i ),…, (L n , t n )}. (L i , t i ) represents the time t when the user appears at the location Li of a certain base station i . The trajectories of mobil...

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Abstract

The present invention involves a user classification method and system based on the similarity of mobile user trajectory, receiving mobile trajectory data of mobile users and extracted time location information for each mobile user.According to time location information, the average stay time of mobile users at each base station is used as the weight, and FP trees use FP trees to dig the trajectory of the corresponding mobile users frequently.Depending on the weighted support threshold of the trajectory and the presets of the presets, the resident site of the corresponding mobile user is obtained. According to the residential place of each mobile user, the mobile user's trajectory similarity results are calculated through the longest public sub -sequence algorithm, and according to the trajectory, according to the trajectorySimilar results classify mobile users.Based on the average staying time of mobile users at each base station as the weight, the FP tree mining frequently sequence of the trajectory of the corresponding mobile users and finding the resident site of the mobile user can not only ensure the trajectory rules of the user, but also reduce the number of data, reduce the number of data, and reduce the amount of data.Computational complexity.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a user classification method and system based on the similarity of mobile user trajectories. Background technique [0002] With the rapid development of mobile communications and mobile applications, the usage rate and dependence of users on mobile phones are constantly increasing, and mobile operators have accumulated a large number of location data recorded by mobile users in real time. Analyzing the similarity of mobile user locations and extracting similar paths of mobile users has a wide range of applications in travel path prediction, interest area discovery, trajectory clustering, personalized path recommendation, and other fields. [0003] The traditional method for calculating the similarity of mobile user trajectories is to first define the user's location to establish a user-location information model, and then combine the time effect with a collaborative filter...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/24765G06F18/2193G06F18/241
Inventor 陈少权杜翠凤
Owner GCI SCI & TECH
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