Design and Application of Clerical Style Recognition System Based on Data Mining Algorithm
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| Publicat a: | International Journal of Information System Modeling and Design vol. 16, no. 1 (2025), p. 1-18 |
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| Altres autors: | , , |
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IGI Global
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| Accés en línia: | Citation/Abstract Full Text - PDF |
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| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3149558887 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1947-8186 | ||
| 022 | |a 1947-8194 | ||
| 024 | 7 | |a 10.4018/IJISMD.365344 |2 doi | |
| 035 | |a 3149558887 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Jiang, Feifei |u Shaanxi University of Science and Technology, China | |
| 245 | 1 | |a Design and Application of Clerical Style Recognition System Based on Data Mining Algorithm | |
| 260 | |b IGI Global |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Calligraphy | ||
| 653 | |a Digital imaging | ||
| 653 | |a Data mining | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Pattern analysis | ||
| 653 | |a Computer vision | ||
| 653 | |a Character recognition | ||
| 653 | |a Algorithms | ||
| 653 | |a Information systems | ||
| 653 | |a Methods | ||
| 653 | |a Cluster analysis | ||
| 653 | |a Automation | ||
| 653 | |a Clustering | ||
| 653 | |a Digital computers | ||
| 653 | |a Handwriting | ||
| 653 | |a Digitization | ||
| 653 | |a Pattern recognition | ||
| 653 | |a Handwriting recognition | ||
| 653 | |a High definition | ||
| 700 | 1 | |a Ke, Chenghu |u Xi'an University, China | |
| 700 | 1 | |a Zhong, Chenchen |u Shaanxi University of Science and Technology, China | |
| 700 | 1 | |a Zhang, Xiaoling |u City University of Hong Kong, China | |
| 773 | 0 | |t International Journal of Information System Modeling and Design |g vol. 16, no. 1 (2025), p. 1-18 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3149558887/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3149558887/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |