• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.70-76
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• 2010

In this paper, we propose a personalized Chinese character education system using RankBoost algorithm on a smartphone. In a typical Chinese character education scenario, a trainee is supplied with a finite number of Chinese characters as an input set in the beginning. And, as the training session repeats, the trainee will notice her/his difficult characters in the set which she/he hardly answers. Those characters reflect their personalized degrees of difficulty. Our proposed system constructs these personalized degrees of difficulty using RankBoost algorithm. In the beginning, the algorithm start with the set of Chinese characters, of which each is associated with the same weight values. As the training sessions are repeated, the algorithm increase the weights of Chinese characters that the trainee mistakes, thereby eventually constructs the personalized difficulty degrees of Chinese characters. The proposed algorithm maximizes the educational effects by having the trainee exposed to difficult characters more than easy ones.

• Korean Journal of Heritage: History & Science
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• v.50 no.2
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• pp.80-93
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• 2017

This study proposes a new scientific measurement method for damaged epigraph. In this new method, the Chinese characters are converted and coordinates are created for this measurement. This method is then used to decipher partially damaged characters from the parts of the coordinated characters that are damaged and intact. The Chinese characters are divided into 9 square parts by the position of their Chinese Radicals. The unknown characters are then compared and deciphered dependent upon the character shape in 9 square parts that have been created. This method is more scientific, accurate, and makes it easier to find related characters than deciphering through contexts, which is current method. When creating a new software based on this algorithm, it will be especially useful in deciphering an old manuscript or a epigraph that made ancient Chinese characters which are not currently in use. This study will also be helpful in deciphering semi-cursive styled or cursive styled epigraph, as well as semi-cursive styled or cursive styled damaged characters during follow-up research.

• Cross-Cultural Studies
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• v.25
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• pp.529-548
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• 2011

Zu Wen-Zao(朱文藻), Li Tiao-Yuan(李調元), Hong Liang-Ji(洪亮吉), Peng Yuan-Rui(彭元瑞), Qian Dong-Huan(錢東垣), Sun Xing-Yan(孫星衍), Ruan Yuan(阮元), Chen Zhan(陳?), Wu Shi-Fen(嗚式芬), Feng Gui-Fen(馮桂芬), He Shao-Ji(何紹基), Fan Zu-Yin(潘祖蔭) made the contributions to the theoretical construction to the science of Chinese characters in their books "Shuwenxizhuankao(說文繫傳考異)", "Liushufenhao(六書分毫)", "Liushuzhuanzhulu(六書轉注錄)", "Xiqinggujian(西淸古鑒)", "Xiaoeryajiaozheng(小爾雅校證)", "Jiujingzhengsuzikao(九經正俗字考)", "Jiguzhaizhongdingyiqikuanshi(積古齋鐘鼎?器款識)", "Shuwenshengxi(說文聲繫)", "Shuwenjiuzizhengyi(說文解字正義)", "Jungulu(?古錄)", "Shuwenjiuzizhukaozheng (說文解字段注考正)", "Shuowenduanzhubozheng(說文段注駁正)", "Haidongjinshilu(海東金石錄)". They analyzed the rules behind character construction, and tried to find out the nature of Chinese characters, the relationship between Chinese characters, the evolutionary laws of Chinese characters, the characteristic of ancient Chinese characters etc.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.97-107
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• 2002

In this paper, we propose the realization of on-line handwritten Chinese character recognition for mobile personal digital assistants (PDA). We focus on the development of an algorithm having a high recognition performance under the restriction that PDA requires small memory storage and less computational complexity in comparison with PC. Therefore, we use index matching method having computational advantage for fast recognition and we suggest a unit reconstruction method to minimize the memory size to store the character models and to accomodate the various changes in stroke order and stroke number of each person in handwriting Chinese characters. We set up standard model consisting of 1800 characters using a set of pre-defined units. Input data are measured by similarity among candidate characters selected on the basis of stroke numbers and region features after preprocessing and feature extracting. We consider 1800 Chinese characters adopted in the middle and high school in Korea. We take character sets of five person, written in printed style, irrespective of stroke ordering and stroke numbers. As experimental results, we obtained an average recognition time of 0.16 second per character and the successful recognition rate of 94.3% with MIPS R4000 CPU in PDA.

• Journal of Korean Medical classics
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• v.25 no.3
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• pp.51-56
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• 2012

Objective : Every language has twofold aspects in meaning of characters such as 'lead' means guide as a verb and 'lead' means one of metals. Chinese character has several meanings because it is phonogram, even if those are exactly same in shapes. we have concern how different meaning of the character 'Si(死)' is in traditional medical classics. Method : we try to find out the meaning of 'Si' excluding meaning of 'Si', 'death' in "Huangdineijing". Result : 'Si' means 'death' primary and means 'serious disease to death', 'losing consciousness just like death' and so on. Conclusion : Someone who have concern traditional medical classics have to give attentions that characters in classics could get different meanings in same character.

• Journal of Korean Medical classics
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• v.26 no.1
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• pp.47-54
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• 2013

Objective : Each terminology has twofold meaning. Chinese character has several meanings because it is phonogram. Even if exactly same in shapes but the meaning is different. We should be more careful about meaning of the character Fu(胕) in Huangdineijing. Method : We try to find out the meaning of fu excluding meaning of fu(胕), edema(胕腫) in Huangdineijing. Result : Fu means fermented food, edema, sticking, skin, top side of the foot and so on. Conclusion : Someone who have concern traditional medical classics have to give attentions that characters in classics could get different meanings in same character.

• Journal of Korean Medical classics
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• v.22 no.4
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• pp.255-259
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• 2009

The origin of "Fire" in Traditional Chinese Medicine is summed up based on observation and knowledge of natural fire, followed by abstract thinking, of which the outcomes are best symbolized in the character Fire[火]. Because it is an abstract concept, it is hard to give a single and strict definition. Naturally, it would be necessary to analyze and illustrate the origin of 'Fire' from different angles such as broad definition, multi-definition, levels, classifications and effects. The concept of 'Fire' has four meanings in the aspect of the broad definition: first, natural fire; second, the physiological conception of fire; third, the medical conception of fire; fourth, general concept related to fire. In Traditional Chinese Medicine, fire mainly indicates physiologic fire, pathological fire, the fire in the six kinds of natural climate and the fire as one of the properties and the flavors of herbs.

• Journal of the Korea Society for Simulation
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• v.14 no.4
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• pp.9-18
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• 2005

In this paper, the system is implemented in four ways , For those who want to learn Chinese characters using the internet, and To make the learning more interesting and entertaining. Four different learning methods have been provided , using the transition process of Chinese characters, games, animations, and an illustration of the relationships between Chinese Characters and korean letters. The subjects of the evaluation were freshmen polled about the Chinese character learning system. The evaluation methods are : the validity of the research content is evaluated using the Cronbach's coefficient alpha and the performance of the system is evaluated by F-type of Analysis of variance.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.17-23
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• 2016

I think it is valuable to make Chinese ancient character 'Inscriptions on Bones and Tortoise Carapaces' hieroglyphics popular by combining with the digital. Because Chinese characters are ideograms, it has a huge visual effect. When it is thought over meanings with imaged data by using digital technology, it can be easier to conflate Chinese academia and humanities academia, moreover other academia that uses Chinese characters such as jurisprudence or business administration. I believe not only union of humanities and natural science in the global era can be the best example of the word 'consilience', which I mentioned before, but also people enjoy usability from educations, invention of learning contents or open learning to a cultural field by coming into wide use. Futhermore, it should contribute to changing the image of Chinese characteristics from existing difficult stereotype to positive image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2012-2030
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• 2021

Named Entity Recognition (NER) is used to identify entity nouns in the corpus such as Location, Person and Organization, etc. NER is also an important basic of research in various natural language fields. The processing of Chinese NER has some unique difficulties, for example, there is no obvious segmentation boundary between each Chinese character in a Chinese sentence. The Chinese NER task is often combined with Chinese word segmentation, and so on. In response to these problems, we summarize the recognition methods of Chinese NER. In this review, we first introduce the sequence labeling system and evaluation metrics of NER. Then, we divide Chinese NER methods into rule-based methods, statistics-based machine learning methods and deep learning-based methods. Subsequently, we analyze in detail the model framework based on deep learning and the typical Chinese NER methods. Finally, we put forward the current challenges and future research directions of Chinese NER technology.