Cross-platform Predictive Modeling

Cross-Platform Predictive Modeling is a computational framework that integrates and analyzes behavioral, contextual, and temporal data across multiple digital platforms to generate anticipatory insights about user actions, preferences, or system dynamics by leveraging machine learning algorithms trained on harmonized cross-environmental datasets.

7

Publications

269

Citations

30

Authors

12

Institutions

Publications per year

2017–2026

6

Authors

30

  1. XX
    Xing Xie

    Microsoft Research Asia (China), China

    2 publications · 102 citations

    2

    h-index

  2. MZ
    Mengyu Zhou

    Guangxi Medical University, China

    1 publications · 33 citations

    1

    h-index

  3. YS
    Yuanchao Shu

    Zhejiang University, China

    1 publications · 33 citations

    1

    h-index

  4. NH
    Neda Hajiakhoond Bidoki

    University of Central Florida, United States

    1 publications · 12 citations

    1

    h-index

  5. GL
    Gangning Liang

    University of Southern California, United States

    1 publications · 44 citations

    1

    h-index

1–5 of 30

Venues

  1. Information

    1 publications · 12 citations

    1

    h-index

  2. International Journal of Parallel Programming

    1 publications · 20 citations

    1

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 62 citations

    1

    h-index

  4. BMC Bioinformatics

    1 publications · 44 citations

    1

    h-index

  5. ACM Transactions on Intelligent Systems and Technology

    TIST · 1 publications · 40 citations

    1

    h-index

1–5