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Call for papers: Data driven artificial intelligence for human-centric computing

Human-centric Computing and Information Sciences welcomes submissions to the thematic series on ' Data Driven Artificial Intelligence for Human-centric Computing '.

Human-centric computing uses different types of electronic data collection sensors to manage, analyze and integrate assets and resources efficiently to provide better services and communication to humans. Data collected from citizens, assets and devices are processed and analyzed to manage and monitor transportation systems, shopping modes, living houses, information systems and other personal services. Human-centric computing is the wave of the future, which not only helps bring us convenience but also presents new challenges of processing and analyzing massive data. Hence, data processing is an urgent problem that needs to be solved in the area human-centric computing. Traditional data processing mechanisms are less efficient when faced with large amounts of data in human-centric computing. Currently, artificial intelligence (AI) is a new technology for simulating, extending and expanding human intelligence. With the emergence of big data and the gradual maturity of deep learning technologies, AI is gradually becoming a popular solution for cutting-edge technologies. Hence, the data driven artificial intelligence is required to perform data processing and analyzing in human-centric computing.
 

Topics of interest include but are not limited to:

  • AI driven data auditing for human-centric computing
  • AI driven data access control for human-centric computing
  • AI driven key management and distribution scheme
  • AI driven data sharing and data storage scheme for human-centric computing
  • AI driven information retrieval scheme for human-centric computing
  • AI in medicine and autonomous vehicles in human-centric computing
  • Machine learning and data mining for human-centric computing
  • Computer vision for human-centric computing
  • Social network exploration for human-centric computing
  • Human-machine interface for human-centric computing
  • AI driven pervasive computing for human-centric computing
  • AI driven secure communication in human-centric computing
  • AI driven security and privacy issues in human-centric computing


Lead Guest Editor

Han-Chieh Chao, National Dong Hwa University, Taiwan


Guest Editor

Laurence T. Yang, St Francis Xavier University, Canada
Odej Kao, Berlin University of Technology, Germany
Chin-Feng Lai, National Cheng Kung University, Taiwan
 


 

  1. Cascade prediction helps us uncover the basic mechanisms that govern collective human behavior in networks, and it also is very important in extensive other applications, such as viral marketing, online advert...

    Authors: Yun Liu, Zemin Bao, Zhenjiang Zhang, Di Tang and Fei Xiong

    Citation: Human-centric Computing and Information Sciences 2020 10:13

    Content type: Research

    Published on:

  2. In recent years, statistics have confirmed that the number of elderly people is increasing. Aging always has a strong impact on the health of a human being; from a biological of point view, this process usuall...

    Authors: Giovanni Cicceri, Fabrizio De Vita, Dario Bruneo, Giovanni Merlino and Antonio Puliafito

    Citation: Human-centric Computing and Information Sciences 2020 10:5

    Content type: Research

    Published on:

  3. The prediction of individual interpersonal communication skills and personality traits is a critical issue in both industrial and organizational psychology and affective computing. In this study, we invited 11...

    Authors: Hung-Yue Suen, Kuo-En Hung and Chien-Liang Lin

    Citation: Human-centric Computing and Information Sciences 2020 10:3

    Content type: Research

    Published on:

  4. Content cache as well as data cache is vital to Content Centric Network (CCN). A sophisticated cache scheme is necessary but unsatisfied currently. Existing content cache scheme wastes router’s cache capacity ...

    Authors: Hsin-Te Wu, Hsin-Hung Cho, Sheng-Jie Wang and Fan-Hsun Tseng

    Citation: Human-centric Computing and Information Sciences 2019 9:44

    Content type: Research

    Published on:

  5. In order to solve the problem of human motion recognition in multimedia interaction scenarios in virtual reality environment, a motion classification and recognition algorithm based on linear decision and supp...

    Authors: Fuquan Zhang, Tsu-Yang Wu, Jeng-Shyang Pan, Gangyi Ding and Zuoyong Li

    Citation: Human-centric Computing and Information Sciences 2019 9:40

    Content type: Research

    Published on:

  6. Aspect-based sentiment analysis (ABSA) is a powerful way of predicting the sentiment polarity of text in natural language processing. However, understanding human emotions and reasoning from text like a human ...

    Authors: Ning Liu, Bo Shen, Zhenjiang Zhang, Zhiyuan Zhang and Kun Mi

    Citation: Human-centric Computing and Information Sciences 2019 9:35

    Content type: Research

    Published on:

  7. Human-centric computing is becoming an important part of data-driven artificial intelligence (AI) and the importance of data mining under Human-centric computing is getting more and more attention. The rapid d...

    Authors: Chunyong Yin, Biao Zhou, Zhichao Yin and Jin Wang

    Citation: Human-centric Computing and Information Sciences 2019 9:33

    Content type: Research

    Published on:

Annual Journal Metrics

  • Speed
    75 days to first decision for reviewed manuscripts only
    43 days to first decision for all manuscripts
    95 days from submission to acceptance
    16 days from acceptance to publication

    Citation Impact
    3.700 - 2-year Impact Factor
    2.225 - Source Normalized Impact per Paper (SNIP)
    0.661 - SCImago Journal Rank (SJR)

    Usage 
    203,111 downloads
    70 Altmetric mentions

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