论文标题
通过使用传统和深度学习，基于Myers-Briggs类型指标的人格类型
Personality Type Based on Myers-Briggs Type Indicator with Text Posting Style by using Traditional and Deep Learning
论文作者
论文摘要
个性一词可以根据思维，感觉和行为的特征模式的个体差异来表达。这项工作介绍了几种机器学习技术，包括天真的贝叶斯，支持向量机和经常性的神经网络，以根据Myers-Briggs类型指标（MBTI）从文本中预测人格。此外，该项目应用CRISP-DM，该项目代表跨行业的数据挖掘标准过程，以指导学习过程。由于Crisp-DM是一种迭代开发，因此我们采用了敏捷的方法，这是一种快速的迭代软件开发方法，以减少开发周期的最低限度。
The term personality may be expressed in terms of the individual differences in characteristics pattern of thinking, feeling, and behavior. This work presents several machine learning techniques including Naive Bayes, Support Vector Machines, and Recurrent Neural Networks to predict people personality from text based on Myers-Briggs Type Indicator (MBTI). Furthermore, this project applies CRISP-DM, which stands for Cross-Industry Standard Process for Data Mining, to guide the learning process. Since, CRISP-DM is kind of iterative development, we have adopted it with agile methodology, which is a rapid iterative software development method, in order to reduce the development cycle to be minimal.
