基于文本的智能学习情感系统

M. A. Razek, C. Frasson
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引用次数: 15

摘要

如今,每天都有数百万用户使用各种社交媒体系统。这些服务产生大量的信息,在社交网络范式中起着至关重要的作用。正如我们所见,迫切需要一个智能学习情感系统来检测这些信息中的情感。该系统可以适合于理解用户对特定讨论的感受。本文提出了一种基于文本的情感识别方法,利用个人文本数据来识别用户当前的情感。该方法运用支配意义技术对用户情感进行识别。本文报告了基于该算法的测试数据集上令人满意的经验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Text-Based Intelligent Learning Emotion System
Nowadays, millions of users use many social media systems every day. These services produce massive messages, which play a vital role in the social networking paradigm. As we see, an intelligent learning emotion system is desperately needed for detecting emotion among these messages. This system could be suitable in understanding users’ feelings towards particular discussion. This paper proposes a text-based emotion recognition approach that uses personal text data to recognize user’s current emotion. The proposed approach applies Dominant Meaning Technique to recognize user’s emotion. The paper reports promising experiential results on the tested dataset based on the proposed algorithm.
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