Intelligent Visualization and Knowledge Graph Analysis for Trend Detection

This research employs scientometric examination and visual analytics techniques anchored in the Web of Science (WoS) repository to methodically delineate predominant research themes, foundational academic works, and emerging scholarly directions within industry-education integration studies. The investigation seeks to elucidate the discipline's epistemological framework and longitudinal transformation patterns while offering innovative analytical lenses and methodological paradigms to advance theoretical conceptualization and operational innovation in industry-education convergence initiatives. This investigation employs scientometric techniques to systematically map and examine 500 scholarly works on industry-education integration from the Web of Science (WoS) database (2010–2023) using VOSviewer. Through co-occurrence mapping, thematic clustering, and temporal trend analysis, the study identifies dominant research foci, influential contributors, and collaborative networks. This quantitative approach is further supplemented by case study investigations to delineate operational strategies and innovative frameworks for industry-academia synergy. Analysis reveals that research concentration spans five domains: higher education reform, Industry 4.0 alignment, engineering pedagogy enhancement, innovation ecosystems, and sustainability integration. Temporal evolution tracking demonstrates a paradigm shift from foundational theoretical debates to applied technological and implementation studies in recent cycles. Cluster analytics highlight the interdisciplinary nature of industry-education convergence, emphasizing tripartite collaboration among academic institutions, corporate entities, and governmental bodies as pivotal to systemic advancement. By synthesizing research trajectories and thematic priorities, this work establishes a structured knowledge foundation for both theoretical refinement and practical implementation in industry-education integration.

@article{Lv2025,
  title     = {Intelligent Visualization and Knowledge Graph Analysis for Trend Detection},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {10},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Sunan Lv},
  doi       = {10.14569/IJACSA.2025.0161075},
  url       = {https://doi.org/10.14569/IJACSA.2025.0161075}
}