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- W4310448352 abstract "Computational social systems (CSSs) focus on topics such as modeling, simulation, analysis, and understanding of social systems from the quantitative and/or computational perspective. “Systems” can be man–man, man–machine, and machine–machine organizations and adversarial situations as well as social media structures and their dynamics <xref ref-type=bibr rid=ref1 xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>[1]</xref> , <xref ref-type=bibr rid=ref2 xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>[2]</xref> . With the advance of the Internet of Things and communication technologies, various kinds of data from diverse areas can be acquired nowadays. As a result, CSSs are becoming ever more complex. Data-driven CSSs aim to conduct pre-competitive research on architectures and design, modeling, and analysis techniques for cyber-physical systems, with emphasis on making full use of big data and artificial intelligence. These applications include transportation systems, automation, security, smart buildings, smart cities, medical systems, energy generation and distribution, water distribution, agriculture, military systems, process control, asset management, and robotics <xref ref-type=bibr rid=ref3 xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>[3]</xref> , <xref ref-type=bibr rid=ref4 xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>[4]</xref> , <xref ref-type=bibr rid=ref5 xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>[5]</xref> . However, due to the progressive transformation from host-centric networking to information-centric networking, CSSs pose fundamental challenges in multiple aspects, such as heterogeneous data generation, efficient data sensing and collection, real-time data processing, and greater request arrival rates. Thus, there is a great need for a powerful way that can deal with emerging issues in data-driven CSSs more efficiently and effectively in the age of big data." @default.
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- W4310448352 date "2022-12-01" @default.
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- W4310448352 title "Guest Editorial Special Issue on Advanced Cognitive Computing for Data-Driven Computational Social Systems" @default.
- W4310448352 doi "https://doi.org/10.1109/tcss.2022.3219608" @default.
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