Artificial intelligence based social robots in the process of student mental health diagnosis

IF 2.8 3区 计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS
Jinyi Zhang, Tianchen Chen
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引用次数: 0

Abstract

This paper in order to achieve the application of artificial intelligence based social robots in the process of student mental health diagnosis. When designing the architecture of social robots, factors such as interactivity, adaptability, and scalability were taken into consideration to ensure that they possess human like interaction characteristics and flexibility. Subsequently, a model was constructed based on deep learning technology to achieve functions such as sentiment classification, text mining, and optimization strategies. The input data set of the training model comes from the user’s interaction records and behavior data on the Internet social platform, as well as the user’s feedback information in the process of using the robot. The research on psychological data classification has constructed corresponding algorithms based on pointer networks and text models to achieve text feature extraction and classification. The psychological emotion mining module extracts emotional states from user discourse and maps them to corresponding categories of psychological problems. Finally, based on the user input question content, classify and optimize psychological problems. Research has shown that the robot has certain accuracy and practicality in data classification and student mental health diagnosis.

基于人工智能的社交机器人在学生心理健康诊断过程中的应用
本文旨在实现基于人工智能的社交机器人在学生心理健康诊断过程中的应用。在设计社交机器人的架构时,考虑了交互性、适应性和可扩展性等因素,以确保其具备与人类相似的交互特性和灵活性。随后,基于深度学习技术构建了一个模型,以实现情感分类、文本挖掘和优化策略等功能。训练模型的输入数据集来自用户在互联网社交平台上的交互记录和行为数据,以及用户在使用机器人过程中的反馈信息。心理数据分类研究基于指针网络和文本模型构建了相应的算法,实现文本特征提取和分类。心理情绪挖掘模块从用户话语中提取情绪状态,并将其映射到相应的心理问题类别。最后,基于用户输入的问题内容,对心理问题进行分类和优化。研究表明,该机器人在数据分类和学生心理健康诊断方面具有一定的准确性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Entertainment Computing
Entertainment Computing Computer Science-Human-Computer Interaction
CiteScore
5.90
自引率
7.10%
发文量
66
期刊介绍: Entertainment Computing publishes original, peer-reviewed research articles and serves as a forum for stimulating and disseminating innovative research ideas, emerging technologies, empirical investigations, state-of-the-art methods and tools in all aspects of digital entertainment, new media, entertainment computing, gaming, robotics, toys and applications among researchers, engineers, social scientists, artists and practitioners. Theoretical, technical, empirical, survey articles and case studies are all appropriate to the journal.
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