Knowledge Commons of Institute of Automation,CAS
Modeling Digital Personality: A Fuzzy-Logic-Based Myers-Briggs Type Indicator for Fine-Grained Analytics of Digital Human | |
Tan Wang1; Peijun Ye2; Hongqiang Lv1; Weichao Gong2; Hao Lu2; Fei-Yue Wang2 | |
发表期刊 | IEEE Transactions on Computational Social Systems |
ISSN | 2329-924X |
2024 | |
卷号 | 11期号:1页码:1096-1107 |
文章类型 | Regular Paper |
摘要 | Digital human in cyberspace can help provide humanized services in specific applications, such as question & answer systems, recommender systems, chatter robots, and intelligent assistants. While most researches focus on behavior analytics, few of them integrate the personality that is also a closely related factor. As a classic indicator for personality representation, Myers–Briggs type indicator (MBTI) categorizes an individual into mutually exclusive types from four dichotomous axes (extraversion versus introversion, sensing versus intuition, thinking versus feeling, judging versus perceiving). Traditional recognition method using MBTI simply measures the user's preference frequency in each axis through questionnaires, treating the dominant value as the identified result. Such a paradigm, however, represents all the people with only 16 types and cannot distinguish heterogeneous users clearly. This article proposes a novel personality recognition method using fuzzy logic. Different from previous classifications, our new method categorizes the individual in a continuous space and represents one's personality in a more fine-grained level. We have designed comparative psychological tests for 77 people. The validation experiments on such tests indicate that the fuzzy-logic-based method is not only consistent with the classic MBTI tests (in the sense of defuzzification) but also provides the uncertainty for each personality type. Therefore, it can be viewed as a generalization of the classic MBTI tests and promotes the representation of individual's heterogeneity for fine-grained analytics of digital human. |
关键词 | Digital Human Digital Personality Fuzzy Logic Reasoning Fuzzy Personality Recognition Myers–Briggs Type Indicator (MBTI) |
学科门类 | 工学::控制科学与工程 ; 工学::计算机科学与技术(可授工学、理学学位) |
DOI | 10.1109/TCSS.2023.3245127 |
URL | 查看原文 |
收录类别 | SCIE |
七大方向——子方向分类 | 智能交互 |
国重实验室规划方向分类 | 人机混合智能 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57122 |
专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 |
通讯作者 | Peijun Ye |
作者单位 | 1.Macau University of Science and Technology 2.Institute of Automation, Chinese Academy of Sciences |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Tan Wang,Peijun Ye,Hongqiang Lv,et al. Modeling Digital Personality: A Fuzzy-Logic-Based Myers-Briggs Type Indicator for Fine-Grained Analytics of Digital Human[J]. IEEE Transactions on Computational Social Systems,2024,11(1):1096-1107. |
APA | Tan Wang,Peijun Ye,Hongqiang Lv,Weichao Gong,Hao Lu,&Fei-Yue Wang.(2024).Modeling Digital Personality: A Fuzzy-Logic-Based Myers-Briggs Type Indicator for Fine-Grained Analytics of Digital Human.IEEE Transactions on Computational Social Systems,11(1),1096-1107. |
MLA | Tan Wang,et al."Modeling Digital Personality: A Fuzzy-Logic-Based Myers-Briggs Type Indicator for Fine-Grained Analytics of Digital Human".IEEE Transactions on Computational Social Systems 11.1(2024):1096-1107. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
2024-TCSS-Modeling_D(91KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论