计算机科学

计算机科学 ›› 2024, Vol. 51 ›› Issue (7): 49-58.doi: 10.11896/jsjkx.221200039

• 数据库&大数据&数据科学 • 上一篇    下一篇

城市大数据认知计算研究与应用进展

刘伟1, 孙佳2, 王鹏2, 陈亚繁1   

  1. 1 北京信息科技大学自动化学院 北京 100192
    2 中国科学院自动化研究所复杂系统管理与控制国家重点实验室 北京 100190
  • 收稿日期:2022-12-06 修回日期:2024-05-09 出版日期:2024-07-15 发布日期:2024-07-10
  • 通讯作者: 王鹏(peng_wang@ia.ac.cn)
  • 作者简介:(willie@bistu.edu.cn)
  • 基金资助:
    国家重点研发计划(2023YFC2600062)

Development on Methods and Applications of Cognitive Computing of Urban Big Data

LIU Wei1, SUN Jia2, WANG Peng2, CHEN Yafan1   

  1. 1 School of Automation,Beijing Information and Science & Technology University,Beijing 100192,China
    2 State Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China
  • Received:2022-12-06 Revised:2024-05-09 Online:2024-07-15 Published:2024-07-10
  • About author:LIU Wei,born in 1986,Ph.D,associate professor.Her main research interests include machine learning and natural language processing.
    WANG Peng,born in 1981,Ph.D,professor,Ph.D supervisor,is a member of CCF(No.66049S).His main research interests include perception and control of robot human brain and so on.
  • Supported by:
    National Key Research and Development Program of China(2023YFC2600062).

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摘要： 城市大数据为城市运行状态估计与综合决策提供理论与行动支撑,而其多源异构、耦合度低及动态变化等特点给传统的集成分析带来极大挑战。认知计算适用于时变多维、复杂多样数据的分析与挖掘,并可对问题进行自适应学习与进化,是解决城市大数据问题的重要途径。文中以城市大数据为背景,根据城市大数据的不同类型结构等特点,针对性地按照认知流程的4个环节对相应处理方法进行归纳,并进一步从知识驱动、数据驱动以及知识与数据协同驱动的角度,对上述具体方法进行概念级分类。最终形成城市大数据认知流程中不同驱动方式的方法间有机协同,从感知理解到决策行为的城市大数据认知闭环。同时从应用领域多角度综述了城市大数据认知计算的研究与发展现状。最后讨论了认知计算在城市大数据建设领域面临的挑战,并对未来发展趋势和研究方向进行了思考和展望。

关键词: 智慧城市, 大数据, 认知计算, 知识驱动, 数据驱动

Abstract: Urban big data provides theory and action support for urban operation state estimation and comprehensive decision-making,while its characteristics of multi-source heterogeneity,low coupling and dynamic change bring great challenges to traditional integrated analysis.Cognitive computing is applicable to the mining of time-varying multidimensional,complex and diverse data,and can conduct adaptive learning and evolution of problems.Based on the characteristics of different types and structures of urban big data,this paper summarizes the corresponding processing methods according to the four stages of the cognitive process,and further classifies the above specific methods at the conceptual level according two the angle of knowledge driven,data driven and knowledge and data driven.Finally,it forms an organic collaboration between the methods of different driving modes in the cognitive process,and the urban big data cognitive closed-loop from perception and understanding to decision-making behavior.At the same time,it summarizes the research and development status of urban big data cognitive computing in multiple application fields.Finally,the challenges of cognitive computing in the field of urban big data construction are discussed,and the future deve-lopment trend are prospected.

Key words: Smart city, Big data, Cognitive computing, Knowledge-driven, Data-driven

中图分类号: 

  • P208
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