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Design and Application of Clerical Style Recognition System Based on Data Mining Algorithm
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Author(s): Feifei Jiang (Shaanxi University of Science and Technology, China), Chenghu Ke (Xi'an University, China), Chenchen Zhong (Shaanxi University of Science and Technology, China)and Xiaoling Zhang (City University of Hong Kong, China)
Copyright: 2025
Volume: 16
Issue: 1
Pages: 17
Source title:
International Journal of Information System Modeling and Design (IJISMD)
Editor(s)-in-Chief: Thierry O. C. Edoh (RFW-Universtät Bonn, (RFW University of Bonn), Bonn/Germany & Ecole Supérieure Multinationale des Telecomunications, Dakar/Senegal)
DOI: 10.4018/IJISMD.365344
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Abstract
With the advancements in high-definition imaging and parallel computing hardware, the analysis of massive visual data has become a key focus in pattern recognition and artificial intelligence. Chinese calligraphy, an integral part of traditional culture, has seen digitization of numerous works stored in digital libraries. However, current automatic calligraphy character recognition technology is limited, necessitating the development of efficient computer vision methods for recognizing calligraphy styles. Data mining, crucial in artificial intelligence, involves extracting valuable knowledge from vast and noisy datasets. Recent simulation results show promising recognition rates for Chinese text images, with an average recognition time of 5 seconds per 100 words. This system significantly improves handwriting recognition accuracy compared to existing algorithms, though further refinement and expansion are needed for optimal functionality.
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