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A multi-marker prediction method for user personal character based on the lowest threshold

A prediction method and user technology, applied in special data processing applications, instruments, website content management, etc., can solve the problem of low overall accuracy, subjectivity of feature weight user personal character mark threshold allocation, poor applicability, etc. question

Inactive Publication Date: 2019-04-16
JILIN UNIV
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  • Claims
  • Application Information

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Problems solved by technology

[0011] The technical problem to be solved by the present invention is to overcome the problems of low overall accuracy, poor applicability, too subjective distribution of feature weights and user personal character mark thresholds existing in the prior art, and propose a user personal character method of prediction

Method used

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  • A multi-marker prediction method for user personal character based on the lowest threshold
  • A multi-marker prediction method for user personal character based on the lowest threshold
  • A multi-marker prediction method for user personal character based on the lowest threshold

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Experimental program
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Embodiment

[0149] refer to figure 2 , the steps of the user personal character prediction method described in the present invention are as follows:

[0150] 1. See image 3 , the feature parsing and representation module realizes the parsing and representation of the characteristics related to the user's personal character, and the steps are as follows:

[0151] (1) Taking the Sina Weibo webpage with the URL http: / / weibo.com / jietangthu as an example, the webpage is as follows Figure 7 As shown, the Sina Weibo user’s initial user feature set, relationship feature set, interest feature set, and posting status set are obtained through the Sina Weibo API;

[0152] (2) Preprocessing the user's personal feature set and relationship feature set:

[0153] 1) Convert the date of the user’s registration on Weibo based on a certain time point into the number of days the user has registered on the Weibo account, that is, the number of days the user is active, recorded as: actDays, and add it to...

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Abstract

The invention discloses a prediction method for user personal characters. The problems that an existing prediction method for user personal characters is not high in whole precision and not high in applicability, and distribution of feature weights and user personal character marking threshold values is excessively subjective are solved. The prediction method comprises the steps of (1) achieving analysis and expression of relevant feature sets of the user personal characters through a feature analysis and expression module, (2) achieving normalization of multivariate data types through a feature analysis and preprocessing module, (3) achieving distribution of the feature weights and determination of the user personal character marking minimum threshold value through a parameter study module, and (4) achieving prediction of the user personal characters through a user personal character prediction module.

Description

technical field [0001] The present invention relates to a method for predicting user personal character in the field of social network individual cognition, more precisely, the present invention relates to a method for predicting user personal character. Background technique [0002] The rapid development of social networks provides rich information for user behavior learning and modeling. The user's personal character is mainly reflected in the attitude towards things and the words and deeds adopted, and plays a hidden role in the user's interactive behavior. [0003] At present, there are mainly two methods to realize the prediction of users' personal character: one is to use machine learning and statistical analysis methods to model it based only on the basic network structure characteristics of users; the other is to model it based on the basic network characteristics of users , introduce dictionary resources, analyze the linguistic characteristics of users, extract the...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/9535G06F16/958
CPCG06F16/9535G06F16/958
Inventor 王英左万利王萌萌王鑫彭涛田中生赵秋月
Owner JILIN UNIV
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