Big Data Mining and Analytics

ISSN 2096-0654 e-ISSN 2097-406X CN 10-1514/G2
Editors-in-Chief: Yi Pan, Weimin Zheng
Open Access
Journal Home > Notice List > CFP-Special Issue on Human-Centric Computing and Data-Driven Technologies
Release Time:2024-01-16 Views:312
CFP-Special Issue on Human-Centric Computing and Data-Driven Technologies

Human-centric computing has evolved into a very active research topic with applications in many fields. Individuals and community/crowd are at the core of technology design and development processes, with a specific focus on meeting their unique needs, preferences, and overall well-being. Data-driven technologies, on the other hand, have a long history of being powerful tools for processing, analyzing, and extracting valuable insights from vast datasets.

The convergence of human-centric computing and data-driven technologies sets the stage for remarkable innovation. This integration enables the creation of personalized and tailored solutions that enhance user experiences, optimize computing solutions, enable predictive modeling, and empower individuals and community/crowd in various aspects of their lives. From revolutionizing healthcare outcomes to optimizing service delivery, improving user interaction to facilitating intelligent environments, this amalgamation of human-centric computing and data-driven technologies holds immense promise. Challenges arise from the fact that data are collected and characterized from a wide heterogeneity in terms of source, content, format, domain, and representation. Adequate and successful storage, access, mining, and analytics depend on the emergence of innovative models, intelligent methods, advanced technologies, and cutting-edge implementations. Last but not least, defending digital information against malicious and accidental threats is indispensable and worthy of more research.

The goal of this special issue is to explore a wide variety of research to provide insights into the state-of-the-art technology, architecture, mechanism, protocol, application, and practice developed for human-centric computing and data-driven technologies. We also seek to foster interdisciplinary discussions and uncover new avenues. Topics of interest include, but are not limited to:

  • Advanced quality assessment, storage, and delivery methods for large-scale datasets
  • Data-driven resource optimization
  • Emerging AI techniques for social network and community/crowd behavioral analysis
  • Enhancing the user experience through fog, edge, or IoT
  • Predictive modeling for healthcare, government, and society in general
  • Sentiment analysis, opinion mining, and recommendation
  • Swarm intelligence and graph data mining
  • Trust computing and privacy preservation

    The authors are requested to submit their full research papers complying with the general scope of the journal. The submitted papers will undergo peer review process before they can be accepted. Notification of acceptance will be communicated as we progress with the review process.

SUBMISSION GUIDELINES

Papers submitted to this journal for possible publication must be original and must not be under consideration for publication in any other journals. Prospective authors should submit an electronic copy of their completed manuscript to https://mc03.manuscriptcentral.com/bdma with manuscript type as “Special Issue on Human-Centric Computing and Data-Driven Technologies”. Further information on the journal is available at: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8254253.

IMPORTANT DATES

Deadline for submissions: June 30, 2024          

GUEST EDITORS

Prof. Yuan Tian, Nanjing Institute of Technology, China. Email: ytian@njit.edu.cn

Prof. Muhammad Khurram Khan, King Saud University, Saudi Arabia. Email: mkhurram@ksu.edu.sa

Prof. Zhaoqing Pan, Tianjin University, China. Email: zhaoqingpan@tju.edu.cn

Prof. Vidyasagar Potdar, Curtin University, Australia. Email: v.potdar@curtin.edu.au