Personality Traits Identification Using Rough Sets Based Machine Learning

Umang Gupta, N. Chatterjee
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引用次数: 21

Abstract

Prediction of human behavior from his/her traits has long been sought by cognitive scientists. Human traits are often embedded in one's writings. Although some work has been done on identification of traits from essays, very little work can be found on extracting personality traits from written texts. Psychological studies suggest that extraction and prediction of rules from a data has been long pursued, and several methods have been proposed. In the present work we used Rough sets to extract the rules for prediction of personality traits. Rough Set is a comparatively recent method that has been effective in various fields such as medical, geological and other fields where intelligent decision making is required. Our experiments with rough sets in predicting personality traits produced encouraging results.
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基于粗糙集的机器学习的人格特征识别
长期以来,认知科学家一直在寻求从他/她的特征中预测人类的行为。一个人的作品中往往蕴含着人性的特质。虽然在从文章中识别个性特征方面已经做了一些工作,但从书面文本中提取个性特征的工作却很少。心理学研究表明,从数据中提取和预测规则的研究已经进行了很长时间,并提出了几种方法。在本工作中,我们使用粗糙集来提取人格特征的预测规则。粗糙集是一种相对较新的方法,在医学、地质等需要智能决策的领域中得到了很好的应用。我们用粗糙集来预测性格特征的实验产生了令人鼓舞的结果。
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