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User classifying 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 high computational complexity, catastrophic execution of data sparsity algorithms, and appearance of sparse matrices

Active Publication Date: 2017-05-31
GCI SCI & TECH
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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 classifying method and system based on mobile user trajectory similarity
  • User classifying method and system based on mobile user trajectory similarity
  • User classifying 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 invention relates to a user classifying method and system based on mobile user trajectory similarity; the method comprises: receiving motion trajectory data of mobile users and extracting time-position information of each mobile user; using FP (frequent pattern) tree to mine a trajectory frequent sequence of the corresponding mobile user by using average stay length of the mobile user at each base station as a weight according to the time-position information; extracting according to the trajectory frequent sequence and a preset weighted support threshold to obtain a resident site of the corresponding mobile user, calculating trajectory similarity results of the mobile users through longest common subsequence algorithm according to the resident sites of the mobile users, and classifying the mobile users according to the trajectory similarity results. The FP tree is used to mine the trajectory frequent sequence of the corresponding mobile user and find the resident site of the mobile user by using the average stay length of the mobile user at each base station as a weight, user trajectory law can be guaranteed, data quantity can also be decreased, and calculation complexity is reduced.

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 Applications(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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