System and method for predicting individual core characteristics based on multi-modal data

Abstract

The invention belongs to the technical field of computer software, and discloses a system and method for predicting individual core characteristics based on multi-modal data. The identification moduleis used for identifying the multi-modal data variables closely related to each core trait as input characteristics of the prediction model; the prediction model establishing module is used for establishing a prediction model with an actual prediction effect on a corresponding target variable by fusing the multi-modal characteristics through a machine learning means; and the verification module isused for keeping a prediction model with good reliability and validity as a core of the prediction system after the internal cross verification of the samples and the external verification of the cross samples, carrying a matched intelligent platform, leading out an evaluation report and visually displaying corresponding results. By using the feature set after multi-modal fusion to predict the target variable, not only the interaction among the modal data can be considered, but also the advantages of the modal indexes can be brought into full play, and the prediction effectiveness of the target variable can be increased.

Description

technical field [0001] The invention belongs to the technical field of computer software, and in particular relates to a system and method for predicting individual core traits based on multimodal data. Background technique [0002] At present, the commonly used existing technologies in the industry are as follows: In the course of life development, there are many traits that affect personal physical and mental development and career success. Among them, core traits such as personality, intelligence, emotional regulation and creativity are particularly important. It has always been the focus of people's interest to predict and evaluate various core traits through some objective quantitative indicators. At present, the use of different types of data such as brain imaging or genes to predict and evaluate individual core traits is often based on a single modality of data. With the wide application of machine learning and data acquisition technologies such as genetic testing and...

AI Technical Summary

Problems solved by technology

[0004] (1) Existing technologies often collect a large number of psychological measurement questionnaires to achieve the prediction effect on individual core characteristics, and the process is cumbersome and time-consuming

[0005] (2) Due to the difficulty of collecting data of multiple different modalities in a large sample at the same time, the current prediction schemes for individual core traits often use single-modal data as a predictive indicator, failing to integrate the data hidden in multiple modalities to a greater extent Effective information in the data to achieve better predictions

[0006] (3) Similar technologies usually only provide predictive evaluation reports, but fail to meet the needs of users in other aspects, such as the need for social networking based on similarity and the need to receive targeted information

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