System and method for automatically labeling child-bearing cases based on meta-learning

Abstract

The invention relates to a meta-learning-based child-bearing case automatic labeling system and method, and the system comprises a preprocessing module which is used for processing a received child-bearing case text to obtain a child-bearing case statement; a problem description statement recognition module which is used for receiving the childbearing case statement, performing recognition by calling a first model, and generating a to-be-labeled statement; an influence factor classification module which is used for receiving to-be-labeled statements, calling a second model for classification, and obtaining influence factor category information to which the statements belong; and a specific annotation category classification module which is used for receiving the to-be-annotated statement with the influence factor category information, calling a classifier corresponding to the influence factor category, and generating a specific annotation category of the to-be-annotated statement. According to the method, rapid and automatic labeling can be performed on the childbearing cases, and the labeling efficiency and labeling accuracy of childbearing case data can be improved conveniently.

Description

technical field [0001] The invention belongs to the field of automatic text labeling, and in particular relates to a system and method for automatic labeling of education cases based on meta-learning. Background technique [0002] Education cases, also known as moral education cases, refer to the case text data related to the moral education of primary and secondary school students. It is characterized by the textual descriptions of the problem behaviors shown by the students, the textual descriptions of the students’ personal situations, and the specifics of these cases. Problem performance, solutions taken by teachers and parents. These educating case data contain rich knowledge and experience, and play an important role in solving the moral education problems that students often encounter. [0003] A typical parenting case is as follows: [0004] Education for children from single parent families [0005] Shaanxi Province [0006] I am a young teacher who grew up happ...

AI Technical Summary

Problems solved by technology

[0018] The advantage of labeling case data by manual labeling with the help of labeling tools is that the quality of the labeling data is high, but there are also some disadvantages

On the one hand, it needs to invest a lot of manpower and material resources, and at the same time, it needs to be labeled by personnel with relevant professional knowledge, and the labeling ability of the labelers will affect the final labeling results, and has a certain degree of subjectivity; on the other hand, this labeling Low efficiency, not suitable for labeling a large amount of text data

[0019] In addition, currently there are few education case data collected, and in the case of many classification categories, if a classification model is trained directly based on these labeled data, the model cannot be fully trained, resulting in the accuracy of the model classification. lower

Images