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User attribute and social network detection system based on space-time locus

A spatiotemporal trajectory, social network technology, applied in forecasting, data processing applications, special data processing applications, etc., can solve problems such as difficulty in obtaining social network information, and achieve the effect of avoiding data acquisition problems, improving applicability, and improving forecasting ability.

Active Publication Date: 2017-04-26
XI AN JIAOTONG UNIV
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AI Technical Summary

Problems solved by technology

However, due to privacy issues, social network information is difficult to obtain in practical applications

Method used

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  • User attribute and social network detection system based on space-time locus
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  • User attribute and social network detection system based on space-time locus

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Embodiment Construction

[0034] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the implementation manners of the present invention will be described in detail below in conjunction with the drawings and embodiments.

[0035] like figure 1 As shown, the system consists of four subsystems, which are data processing subsystem, social network modeling subsystem, feature extraction subsystem and classification prediction subsystem. The input data of the system is the user's spatio-temporal trajectory data, which includes three parts: user identification, geographical location identification and time identification. That is, each row indicates that a certain user has been to a certain place at a certain time.

[0036] It is worth noting that the attributes of some users in the input data are unknown (called target users), and the attributes of these users need to be predicted. For this purpose, some spatiotemporal trajectory data of u...

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Abstract

The invention provides a user attribute and social network detection system based on space-time locus. A user behavior mode is analyzed to predict true identity attributes of a user, and data processing, social network modeling, characteristic extraction and classification prediction subsystems are included; space-time locus data is analyzed; according to the space-time locus data, an original method based on the point mutual information is proposed to establish a social network model of the user; an original non-negative tensor factorization (NTF) algorithm is proposed to automatically extract hidden characteristics of the user; the hidden characteristics of the user are utilized to predict user attributes through utilizing multiple types of classifiers. The system is advantaged in that the system is applied to user attribute authenticity detection, can be further applied to user social network detection and can be further applied to precise information push and friendly recommendation according to predicted attributes and the social network.

Description

technical field [0001] The invention belongs to the technical field of data mining, in particular to a user attribute and social network detection system based on time-space trajectory. Background technique [0002] With the application and development of Internet technology, there are more and more Internet users. The Internet is virtual, and the user's information on the Internet is not necessarily its real attribute. In order to improve the security of the Internet, it is necessary to ensure the authenticity of the user's identity. In addition, understanding the social relationship of users also has important applications in issues such as maintaining public safety and anti-terrorism. [0003] The development of mobile communication technology and the rapid popularization of smart mobile devices (such as smart phones and tablet computers) have made the connection between mobile devices and users closer and closer, and many mobile devices and APPs can record user actions....

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06F17/30G06K9/62
CPCG06F16/9537G06Q10/04G06F18/2431
Inventor 王平辉孙飞扬王迪管晓宏陶敬张岩曹鹏飞贾鹏胡小雨曹宇兰林
Owner XI AN JIAOTONG UNIV
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