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Multiple knowledge representation for big data artificial intelligence: framework, applications, and case studies

大数据人工智能下的多重知识表达:框架、 应用及案例研究

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摘要

提出一种多重知识表示框架, 探讨了其对推动大数据人工智能技术在各个领域中发展的重要意义及深远影响. 传统知识表达和现代基于深度学习的知识表达通常着眼于利用特定变换方式, 将输入转换为符号编码或者向量. 例如, 知识图谱关注于描述各个概念之间的语义联系, 而深度神经网络更像是感知原始信号输入的工具. 多重知识表达是一种更为先进的人工智能表征框架, 具备更完整的智能功能, 比如原始信号感知、 特征提取及向量化、 知识符号化和逻辑推断. 多重知识表达有如下两点优势: (1) 与现有以深度学习为主导的人工智能技术相比, 具有更强的解释性以及更好的泛化能力; (2) 将多重知识表达集成于现有人工智能技术, 有利于各种表征 (例如原始信号感知以及符号化编码) 发挥互补优势. 我们希望多重知识表达相关研究以及应用能够驱动新一代人工智能蓬勃发展.

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Acknowledgements

The authors thank Drs. Yifan SUN, Linchao ZHU, Xiaohan WANG, and Yu WU for constructive discussions.

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Authors and Affiliations

  1. College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China

    Yi Yang  (杨易), Yueting Zhuang  (庄越挺) & Yunhe Pan  (潘云鹤)

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  1. Yi Yang  (杨易)
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  2. Yueting Zhuang  (庄越挺)
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  3. Yunhe Pan  (潘云鹤)
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Contributions

Yunhe PAN conceptualized the main idea and led the research. Yi YANG and Yueting ZHUANG surveyed the relevant materials. Yi YANG, Yueting ZHUANG, and Yunhe PAN had in-depth discussions; they drafted, revised, and finalized the paper.

Corresponding author

Correspondence to Yi Yang  (杨易).

Ethics declarations

Yi YANG, Yueting ZHUANG, and Yunhe PAN declare that they have no conflict of interest.

Additional information

Project supported by the National Key R&D Program of China (No. 2020AAA0108800)

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Yang, Y., Zhuang, Y. & Pan, Y. Multiple knowledge representation for big data artificial intelligence: framework, applications, and case studies. Front Inform Technol Electron Eng 22, 1551–1558 (2021). https://doi.org/10.1631/FITEE.2100463

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