This research is based on the framework of social constructivism,utilizing the principle of Human Universals as a methodology to compare the similarities and differences between the ideation and formation methods of C...This research is based on the framework of social constructivism,utilizing the principle of Human Universals as a methodology to compare the similarities and differences between the ideation and formation methods of Chinese characters and English alphabets.Through comparative analysis of the ideation of English letters(pictogramme)and the origin of Chinese characters,known as the"Six Categories Theory,"we discover their alignment in terms of social,traditional,and cultural aspects.This suggests that different ethnic groups share common features in terms of life experience,learning cognitive development,and thinking habits.This study also finds that the origins of English letters and Chinese characters share similar linguistic features in their methods of constructing letters/characters,such as pictographic,ideographic,and semantic characteristics.Exploring these commonalities contributes to promoting learning and communication between Chinese and English characters.Additionally,by focusing on socio-cultural aspects,traditional customs,and cognitive learning,this study aims to break away from the traditional linguistic research approach that solely focuses on language differences.This provides a broader perspective and richer dimensions for Chinese and English language learning,facilitating the development of cross-linguistic and cross-cultural communication.展开更多
Hanzi （Chinese characters） has a long history and affluent contents. To promote the popularity of historical and cultural knowledge of Chinese characters, an online program has been launched by Beihang University an...Hanzi （Chinese characters） has a long history and affluent contents. To promote the popularity of historical and cultural knowledge of Chinese characters, an online program has been launched by Beihang University and Beijing Normal University to explain Chinese characters＇ original meanings and evolution processes with vivid and expressive animation videos. Currently, More than 1,000 videos can be accessed through the website “http：//www.chinesecharacter.org/”. Besides these online resources, a human-computer interaction system is also proposed to simulate clerical changes of Chinese characters through computer morphing technology. What we want is to make the teaching and learning of Chinese characters more reasonable, more easily understandable and more interesting.展开更多
In the Chinese character intelligent formation system without Chinese character library, it is possible that the same basic element in different Chinese characters is different in position, size and shape. The geometr...In the Chinese character intelligent formation system without Chinese character library, it is possible that the same basic element in different Chinese characters is different in position, size and shape. The geometry transformation from basic elements to the components of Chinese characters can be realized by affine transformation, the transformation knowledge acquisition is the premise of Chinese character intelligent formation. A novel algorithm is proposed to ac-quire the affine transformation knowledge of basic elements automatically in this paper. The interested region of Chi-nese character image is determined by the structure of the Chinese character. Scale invariant and location invariant of basic element and Chinese character image are extracted with SIFT features, the matching points of the two images are determined according to the principle of Minimum Euclidean distance of eigenvectors. Using corner points as identifi-cation features, calculating the one-way Hausdorff distance between corner points as the similarity measurement from the affine image to the Chinese character sub-image, affine coefficients are determined by optimal similarity. 70244 Chinese characters in National Standards GB18030-2005 character set are taken as the experimental object, all the characters are performed and the experimental courses and results are presented in this paper.展开更多
In recent years, more and more foreigners begin to learn Chinese characters, but they often make typos when using Chinese. The fundamental reason is that they mainly learn Chinese characters from the glyph and pronunc...In recent years, more and more foreigners begin to learn Chinese characters, but they often make typos when using Chinese. The fundamental reason is that they mainly learn Chinese characters from the glyph and pronunciation, but do not master the semantics of Chinese characters. If they can understand the meaning of Chinese characters and form knowledge groups of the characters with relevant meanings, it can effectively improve learning efficiency. We achieve this goal by building a Chinese character semantic knowledge graph (CCSKG). In the process of building the knowledge graph, the semantic computing capacity of HowNet was utilized, and 104,187 associated edges were finally established for 6752 Chinese characters. Thanks to the development of deep learning, OpenHowNet releases the core data of HowNet and provides useful APIs for calculating the similarity between two words based on sememes. Therefore our method combines the advantages of data-driven and knowledge-driven. The proposed method treats Chinese sentences as subgraphs of the CCSKG and uses graph algorithms to correct Chinese typos and achieve good results. The experimental results show that compared with keras-bert and pycorrector + ernie, our method reduces the false acceptance rate by 38.28% and improves the recall rate by 40.91% in the field of learning Chinese as a foreign language. The CCSKG can help to promote Chinese overseas communication and international education.展开更多
文摘This research is based on the framework of social constructivism,utilizing the principle of Human Universals as a methodology to compare the similarities and differences between the ideation and formation methods of Chinese characters and English alphabets.Through comparative analysis of the ideation of English letters(pictogramme)and the origin of Chinese characters,known as the"Six Categories Theory,"we discover their alignment in terms of social,traditional,and cultural aspects.This suggests that different ethnic groups share common features in terms of life experience,learning cognitive development,and thinking habits.This study also finds that the origins of English letters and Chinese characters share similar linguistic features in their methods of constructing letters/characters,such as pictographic,ideographic,and semantic characteristics.Exploring these commonalities contributes to promoting learning and communication between Chinese and English characters.Additionally,by focusing on socio-cultural aspects,traditional customs,and cognitive learning,this study aims to break away from the traditional linguistic research approach that solely focuses on language differences.This provides a broader perspective and richer dimensions for Chinese and English language learning,facilitating the development of cross-linguistic and cross-cultural communication.
文摘Hanzi （Chinese characters） has a long history and affluent contents. To promote the popularity of historical and cultural knowledge of Chinese characters, an online program has been launched by Beihang University and Beijing Normal University to explain Chinese characters＇ original meanings and evolution processes with vivid and expressive animation videos. Currently, More than 1,000 videos can be accessed through the website “http：//www.chinesecharacter.org/”. Besides these online resources, a human-computer interaction system is also proposed to simulate clerical changes of Chinese characters through computer morphing technology. What we want is to make the teaching and learning of Chinese characters more reasonable, more easily understandable and more interesting.
文摘In the Chinese character intelligent formation system without Chinese character library, it is possible that the same basic element in different Chinese characters is different in position, size and shape. The geometry transformation from basic elements to the components of Chinese characters can be realized by affine transformation, the transformation knowledge acquisition is the premise of Chinese character intelligent formation. A novel algorithm is proposed to ac-quire the affine transformation knowledge of basic elements automatically in this paper. The interested region of Chi-nese character image is determined by the structure of the Chinese character. Scale invariant and location invariant of basic element and Chinese character image are extracted with SIFT features, the matching points of the two images are determined according to the principle of Minimum Euclidean distance of eigenvectors. Using corner points as identifi-cation features, calculating the one-way Hausdorff distance between corner points as the similarity measurement from the affine image to the Chinese character sub-image, affine coefficients are determined by optimal similarity. 70244 Chinese characters in National Standards GB18030-2005 character set are taken as the experimental object, all the characters are performed and the experimental courses and results are presented in this paper.
文摘In recent years, more and more foreigners begin to learn Chinese characters, but they often make typos when using Chinese. The fundamental reason is that they mainly learn Chinese characters from the glyph and pronunciation, but do not master the semantics of Chinese characters. If they can understand the meaning of Chinese characters and form knowledge groups of the characters with relevant meanings, it can effectively improve learning efficiency. We achieve this goal by building a Chinese character semantic knowledge graph (CCSKG). In the process of building the knowledge graph, the semantic computing capacity of HowNet was utilized, and 104,187 associated edges were finally established for 6752 Chinese characters. Thanks to the development of deep learning, OpenHowNet releases the core data of HowNet and provides useful APIs for calculating the similarity between two words based on sememes. Therefore our method combines the advantages of data-driven and knowledge-driven. The proposed method treats Chinese sentences as subgraphs of the CCSKG and uses graph algorithms to correct Chinese typos and achieve good results. The experimental results show that compared with keras-bert and pycorrector + ernie, our method reduces the false acceptance rate by 38.28% and improves the recall rate by 40.91% in the field of learning Chinese as a foreign language. The CCSKG can help to promote Chinese overseas communication and international education.
