• The Journal of Korean Medical History
• /
• v.31 no.1
• /
• pp.57-70
• /
• 2018

Much research has already been done on Donguibogam. However, comparison of specific characters was not done because researchers found it difficult to compare different editions of the text in one place. Recently, important editions have been published on the Internet, making comparison possible. In this paper, researchers compare eight editions Donguibogam, including the original edition published in 1613 and seven other editions corrected by the Naeuiwon (Joseon Dynasty National Medical Center). The comparison results were summarized and tabulated. The results of the comparison are analyzed and presented in this article as a chart. The result of comparing the characters and the analyzed graph were in agreement. The authors propose that all written and electronic publications of Donguibogam should refer to other editions implied, quoted or referenced within the text and including with proper citations, and reference the original and first edition. Inadequate referencing will pollute future knowledge of this foundational text of Traditional Korean Medicine and may result in perpetration of mis-information. Based on accumulated knowledge and study of historical Korean Medicine texts, the Namsan edition made a mistake in the editing process. The year of publication of Gabsul-yoengyoeng-gegan Edition needs to be studied again and corrections made where appropriate.

• Language and Information
• /
• v.14 no.2
• /
• pp.159-181
• /
• 2010

This paper presents a hybrid approach to the sentiment analysis of online texts. The sentiment of a text refers to the feelings that the author of a text has towards a certain topic. Many existing approaches employ either a pattern-based approach or a machine learning based approach. The former shows relatively high precision in classifying the sentiments, but suffers from the data sparseness problem, i.e. the lack of patterns. The latter approach shows relatively lower precision, but 100% recall. The approach presented in the current work adopts the merits of both approaches. It combines the pattern-based approach with the machine learning based approach, so that the relatively high precision and high recall can be maintained. Our experiment shows that the hybrid approach improves the F-measure score for more than 50% in comparison with the pattern-based approach and for around 1% comparing with the machine learning based approach. The numerical improvement from the machine learning based approach might not seem to be quite encouraging, but the fact that in the current approach not only the sentiment or the polarity information of sentences but also the additional information such as target of sentiments can be classified makes the current approach promising.

• The Journal of Korean Medical History
• /
• v.27 no.1
• /
• pp.1-7
• /
• 2014

Objectives : By understanding the basic information as a text about the original script, composition and characteristic of "Shanghanlunzhujie" which is included in "Uibang-yuchwi", We are evaluating value and significance of the text today. Methods : First of all, We are finding what the original script is through comparing different editions. Then by concrete analysis about texts, We are going to determine which standards affected "Shanghanlunzhujie" and "Uibang-yuchwi", and which elements included in those texts. In addition, We are figuring out what the characteristics are in the those texts roughly. Through this consideration, We could evaluate value and significance of the text. Results & Conclusions : In the course of research, We found that this publication deserves attention in the hereditary history of the "Shanghanlun" editions. First, the version of the "Shanghanlunzhujie" in the "Uibang-yuchwi" is surely the Won(元) edition. Based on recent research findings, the Won edition is the earliest version of Chengwuji's "Zhujieshanghanlun". Not only does it contain the original contents, it restored the deleted annotations of the Song edition, constituting the most accurate "Shanghanlun" edition closest to the original form of today.

• Journal of the Korea Society for Simulation
• /
• v.11 no.3
• /
• pp.35-48
• /
• 2002

In the work presented here, we describe a method to extract TrueType features for supporting letter recognition. Even if variously existing document processing techniques have been challenged, almost few methods are capable of recognize a letter associated with its TrueType features supporting OCR free, which boost up fast processing time for image text retrieval. By reviewing the mechanism generating digital fonts and birth of TrueType, we realize that each TrueType is drawn by its contour of the glyph table. Hence, we are capable of deriving the segment with density for a letter with a specific TrueType, defined by the number of occurrence over a segment width. A certain number of occurrence appears frequently often due to the fixed segment width. We utilize letter recognition by comparing TrueType feature library of a letter with that from input word images. Experiments have been carried out to justify robustness of the proposed method showing acceptable results.

• Journal of Information Technology Services
• /
• v.2 no.2
• /
• pp.87-95
• /
• 2003

With the increasing proliferation of World Wide Web, electronic mail systems have become very widely used communication tools. Researches on e-mail classification have been very important in that e-mail classification system is a major engine for e-mail response management systems which mine unstructured e-mail messages and automatically categorize them. in this research we develop e-mail classifiers for e-mail Response Management Systems (ERMS) using naive bayesian learning and centroid-based classification. We analyze which method performs better under which conditions, comparing classification accuracies which may depend on the structure, the size of training data set and number of classes, using the different data set of an on-line shopping mall and a credit card company. The developed e-mail classifiers have been successfully implemented in practice. The experimental results show that naive bayesian learning performs better, while centroid-based classification is more robust in terms of classification accuracy.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.05a
• /
• pp.401-403
• /
• 2019

In this paper, we propose a generative adversarial networks (GAN) based text-to-image generating method. In many natural language processing tasks, which word expressions are determined by their term frequency -inverse document frequency scores. Word2Vec is a type of neural network model that, in the case of an unlabeled corpus, produces a vector that expresses semantics for words in the corpus and an image is generated by GAN training according to the obtained vector. Thanks to the understanding of the word we can generate higher and more realistic images. Our GAN structure is based on deep convolution neural networks and pixel recurrent neural networks. Comparing the generated image with the real image, we get about 88% similarity on the Oxford-102 flowers dataset.

• International Journal of Contents
• /
• v.12 no.1
• /
• pp.54-59
• /
• 2016

The purpose of this paper is to discover how the use of digital applications can affect students' attitudes toward positive classroom participation and performance in learning a foreign language. Participants of this study were 128 students who took a foreign language class at a high school in central Korea. To find out students' perceptions and attitudes toward the effect of using a digital application for their foreign language study, online questionnaire and focus-group interview were conducted. Our research findings revealed that these students could engage in active language learning and experience learning improvement while studying a foreign language with digital applications. The improvement was possible by creating more interactive activities and quizzes. In addition, the digital application provided students immediate feedback. It gave students and teachers various motivations beyond the traditional 'chalk and talk' format of text-only-classes. This study provides an overview of the usefulness of digital application. In addition, it provides understanding for students' perceptions and involvement using digital application in a foreign language classroom.

• Journal for History of Mathematics
• /
• v.11 no.1
• /
• pp.27-35
• /
• 1998

As Chinese philosophy has developed by commentary for the original texts, the Nine Chapters has been greatly improved by the commentary given by Liu Hui and it was transformed from an arithmetic text to Mathematics. Comparing his commentary and Chinese philosophical development up to his date, we conclude that Liu Hui was able to make such a great leap by his thorough understanding of philosophical development.

• Proceedings of the Zoological Society Korea Conference
• /
• 1999.10b
• /
• pp.257.1-257
• /
• 1999

No Abstract, See Full Text

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.7
• /
• pp.1713-1723
• /
• 1999

Optical character recognition(OCR) might be the most plausible method in building database out of printed matters. This paper describes the points to be considered when one selects an OCR system in order to build database. Based on the considerations, we evaluated four commercial OCR systems, and chose one which shows the best recognition rate to build OCT-text database. The subject text, the KT-test collection, is a set of abstracts from proceedings of different printing quality, fonts, and formats. KT-test collection is also provided with typed text database. Recognition rate was calculated by comparing the recognition result with the typed text. No preprocessing such as learning and slant correction was applied to the recognition process in order to simulate a practical environment. The result shows 90.5% of character recognition rate over 970 abstracts. This recognition rate is still insufficient for practical use. The errors in OCR texts are different from those of manually typed texts. In this paper, we classify the errors in OCR texts for the further research.