对汉字的认知研究不仅是认知科学,也是计算机科学特别是人工智能领域中的一个研究热点。但是,目前汉字认知的计算机模拟研究还相对滞后。该文采用自组织特征映射网络(Self-organizing Feature Map, SOFM)和自适应谐振理论(Adaptive Resonance Theory, ART)相结合的方法,构建汉字认知过程的发展模型,对汉字字形认知的发展过程(学习发展历程)进行了计算机模拟,以便研究汉字字形学习过程中的某些认知发展规律。模型通过训练,显示出了汉字认知发展过程中的某些规律。
Abstract
The research of Chinese characters cognition is an important aspect of cognitive science and computer science, especially artificial intelligence. According to the traits of Chinese characters, this paper proposes a Chinese characters font cognition model based on self-organizing neural network and adaptive resonance theory (ART). This model attempts to simulate the development process of Chinese characters cognition so as to reveal some essential rules in human learning of Chinese character. Through training and testing this model, the simulation results suggest that the model is able to account for some empirical results in Chinese character cognition development.
关键词
计算机应用 /
中文信息处理 /
认知科学 /
人工智能 /
汉字认知发展 /
计算机模拟 /
自组织模型 /
自适应谐振理论
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Key words
computer application /
Chinese information processing /
cognitive science /
artificial intelligence /
cognitive development of Chinese characters /
computer simulation /
self-organizing map /
adaptive resonance theory
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参考文献
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脚注
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基金
北京市教委重点学科共建基金资助项目(XK100080537)
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