Personality characteristic prediction method and system based on network behaviors

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 on behavior time and timing, and can not realize automatic prediction of personality traits, so as to save human resource costs and reduce inaccurate personality prediction Effect

Active Publication Date: 2019-08-13
SHANDONG UNIV
View PDF4 Cites 5 Cited by
  • 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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Personality characteristic prediction method and system based on network behaviors
  • Personality characteristic prediction method and system based on network behaviors
  • Personality characteristic prediction method and system based on network behaviors

Examples

Experimental program
Comparison scheme
Effect test

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.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a personality characteristic prediction method and system based on network behaviors. The method comprises the steps of obtaining user behavior data; marking personality characteristics of users; performing data preprocessing and feature extraction on the acquired data; performing data integration on the data features extracted in the set time period according to the occurrence time sequence to form behavior vector features containing a time sequence relation; and making the behavior vector characteristics of the users correspond to the marked personality characteristics, inputting the corresponding data into a long-short-term memory model for prediction, and outputting a prediction result of the personality characteristics. The method has the advantages that personality characteristics of users can be automatically predicted; heterogeneous data of a social platform are used, and automatic calculation and prediction of the personality of the users are achieved.

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap