摘要:随着机器学习和大数据技术的应用发展，基于语义分析的情感计算与分析技术在研究人类的感知、注意力、记忆、决策、社会交流等诸多方面起着重大作用，它不仅影响到了人工智能技术的发展，还影响到了人/机交互的方式，并受到学术界以及企业界的广泛关注.在针对情感定义以及相关90多种情感模型分析的基础上，归纳并提出了目前情感分析领域中存在的6项关键性问题与挑战，其中主要包括：情感的来源与本质特征的表示问题；多模态的情感计算问题；外部因素对情感演化过程的影响度量问题；情感的个性化度量问题；情感群体化特征与传播动力学机制问题以及细微情感的表达、算法改进与优化等问题.同时，针对其中的关键问题与技术挑战进行了理论探讨、技术分析、实际应用以及当前工作进展与趋势分析，从而为深入研究和解决基于语义分析条件下的情感计算提供了新的研究线索与方向.



Abstract:With the development of machine learning and application of big data, semantic-based emotional computing and analysis technology plays a significant role in the research on human perception, attention, memory, decision-making, and social communication. It affects not only the development in artificial intelligence technology, but also human/machine interaction and smart robot technology, therefore drawing widespread interest from the academic and business communities. In this paper, based on the definition of affection and the analysis of more than 90 emotional models, six vital problems and challenges in emotional computing are summarized as follows:where is emotion stem from and how to represent their essential features; how to analyze and compute the emotion under the multi-model environment; how to measure the influence of external factors on the process of emotional evolution; how to measure individual emotion by various of personalized characteristic; how to measure the crowed psychology and emotion and to analyze the mechanism about propagation dynamics; and how to express the subtle emotion and optimize algorithms. Meanwhile, some theoretical research, technical analysis and practical application are brought up to introduce the current work progress and trend for these technical challenges in order to provide new research clues and directions for further study in the field of the semantic-based emotional computing.



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