Global Research Trends and Citation Impact in Ceramic Decorative Pattern Art: A Comprehensive Bibliometric Analysis (1978–2024)
Keywords:
Deep Learning, Ensemble Models, Deep Neural Networks (Dnns), Recurrent Neural Networks (Rnns) And Feature Extraction.Abstract
Ceramic decorative patterns hold cultural and aesthetic value, blending craftsmanship with symbolism. Recent research integrates traditional art history with technologies like computer-aided design and pattern recognition, emphasizing the need to understand global research trends and citation impact. A bibliometric analysis of 395 publications (1978-2024) from the Web of Science explored citation impact, publication trends, and keyword co-occurrence, mapping themes such as cross-cultural exchange, craftsmanship, and technological innovation. Research output surged after 2008, peaking in 2014-2020 with 9.28 citations per article. Studies combining traditional and modern design, especially in cross-cultural contexts, had higher citations. Recently, emerging technologies like deep learning have gained attention. While traditional elements remain central, modern technologies are driving newresearch directions. Future studies should leverage these innovations to reinterpret ceramic art, with interdisciplinary approaches being crucial.Downloads
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