Applying Multi-Dimensional Self-Organizing Feature Maps (SOFM) to construct the Relationship of Chinese Characters

• Main Authors: CHANG JUI LUNG, 張瑞隆
• Other Authors: K.T.SUN
• Format: Others
• Language: zh-TW
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/51982779949484230245

碩士 === 臺南師範學院 === 資訊教育研究所 === 87 === The self-organizing feature maps（SOFM）net is one kind of unsupervised learning neural network. When the SOFM had learned the features of training patterns, the neurons, contain similar features, are close together. In this paper, we propose a multi-dimensional Self-Organizing Feature Maps (SOFM) to construct the relationship of Chinese characters. The proposed model extends the traditional one-dimensional relationship of Chinese characters （e.g. in a Chinese dictionary, Chinese characters with one same part are put together.）and then becomes a useful tool for orders of characters’education and measurement. Especially, it is useful to teach stroke orders of Chinese characters, Chinese characters with similar characteristics can be retrieved effectively. This technique can enhance the power of computer-assisted instruction（CAI）system and then the system becomes more “intelligent”. Keywords：self-organizing feature maps（SOFM）,stroke orders of Chinese characters, computer-assisted instruction （CAI）.