A method and system for predicting personality traits based on network behavior

A prediction method and behavioral technology, applied in the field of crowd intelligence science, can solve the problems of not considering the influence of personality traits by behavior time and sequence, and the inability to automatically predict personality traits, so as to save human resource costs and reduce inaccurate personality predictions. Effect

Active Publication Date: 2020-08-04
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, most of these works focus on a single data, and do not consider the influence of personality traits on behavior time and timing. At the same time, existing research requires a large number of manual annotations for verification, which cannot achieve the purpose of automatically predicting personality traits

Method used

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  • A method and system for predicting personality traits based on network behavior
  • A method and system for predicting personality traits based on network behavior
  • A method and system for predicting personality traits based on network behavior

Examples

Experimental program
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Embodiment 1

[0035] In one or more embodiments, a method for predicting personality traits based on network behavior is disclosed, comprising the following steps:

[0036] (1) Obtain user behavior data;

[0037] (2) Mark the personality traits of the above-mentioned users;

[0038] (3) Perform data preprocessing and feature extraction on the acquired data;

[0039] (4) According to the chronological order of occurrence, data integration is performed on the data features extracted within the set time period to form behavioral vector features that include temporal relationships;

[0040] (5) Correspond the user's behavior vector features with the labeled personality traits, input the corresponding data into the long-term short-term memory model for prediction, and output the prediction results of personality traits. Among them, the corresponding data refers to the vector formed by connecting the user behavior feature vector and its personality trait score, such as the corresponding vector ...

Embodiment 2

[0099]In one or more implementations, a system for predicting personality traits based on network behavior is disclosed, including:

[0100] A module for obtaining user behavior data;

[0101] A module for labeling the personality traits of the above-mentioned users;

[0102] A module for data preprocessing and feature extraction of acquired data;

[0103] It is used to integrate the data features extracted within the set time period according to the time sequence of occurrence, and form a module of behavior vector features including time series relationship;

[0104] It is used to correspond the user's behavior vector features with the marked personality traits, and input the corresponding data (the vector formed by connecting the user behavior feature vector with its personality trait scores) to the long-term and short-term memory model for prediction, and output the prediction results of personality traits module.

Embodiment 3

[0106] In one or more embodiments, a terminal device is disclosed, which includes a processor and a computer-readable storage medium, the processor is used to implement instructions; the computer-readable storage medium is used to store multiple instructions, and the instructions are suitable for The method for predicting personality traits based on network behavior described in Embodiment 1 is loaded and executed by the processor. For the sake of brevity, details are not repeated here.

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Abstract

The invention discloses a method and system for predicting personality traits based on network behavior, including: acquiring user behavior data; marking the personality traits of the above users; performing data preprocessing and feature extraction on the acquired data; , perform data integration on the data features extracted within the set time period to form behavior vector features including temporal relationships; correspond the user’s behavior vector features with their labeled personality traits, and input the corresponding data into the long-term short-term memory model Make predictions and output predictions of personality traits. The invention has beneficial effects: the personality traits of users can be automatically predicted; and the heterogeneous data of social platforms are used to realize automatic calculation and prediction of user personality.

Description

technical field [0001] The invention belongs to the field of wisdom science and technology, and in particular relates to a method and system for predicting personality traits based on network behavior. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] At present, with the continuous development of social economy and the continuous maturity of technologies such as the Internet, cloud computing, and big data, mobile social networks have become a bridge between the real physical world and virtual cyberspace. Anonymity, people's behavior on the Internet more directly reflects people's activities and emotions in the real world. At the same time, personality measurement has been widely used in more and more fields. For example, personality tests for employment selection, talent selection, and military conscription can help companies or the milita...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/00G06N3/08G06N3/04
CPCG06Q10/04G06Q50/01G06N3/08G06N3/048G06N3/044G06N3/045
Inventor 崔立真王世鹏鹿旭东郭伟
Owner SHANDONG UNIV
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