情感语义分析技术综述及进展

Yimin Wang, Y. Rao, Lianwei Wu
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引用次数: 12

摘要

情感计算给下一代人工智能带来了新的应用机遇和技术挑战,成为一个令人着迷的研究领域。本文定义了包含核心元素和特征向量的情感计算概念,并提出了一些关键问题。基于上述理论,在文本、图像、音频和视频数据等单模态场景下,通过一些特殊算法对主观内容或客观内容进行分类。此外,如何融合这些不同类型的数据,形成多模态分析方法是一个重要的问题,本文对融合策略进行了总结。最后,分析了情感认知和情感生成的发展趋势,为进一步的研究工作提供了新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of Sentiment Semantic Analysis Technology and Progress
Sentiment computing brings some new application opportunities and technique challenges in artificial intelligence of the next generation, and it has become a fascinating research field. In this paper, the conception of sentiment computing with some core elements and feature vectors is defined, and some vital issues are proposed. Based on the theories mentioned above, the subjective content or objective content is classified by some special algorithms in the scenarios of single modal, such as text, image, audio and video data. Furthermore, how to merge these different kinds of data and to form the multimodal analysis methods for emotion detection is an important problem, and the fusion strategy is summarized in the paper. Finally, some trends about the sentiment cognition and sentiment generation are analyzed, which provides new ways for further research work.
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