• The Journal of Sustainable Design and Educational Environment Research
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• v.10 no.2
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• pp.61-72
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• 2011

The purpose of this study is to carry out the research of the satisfaction level of consumers (students and teachers) and managerial characteristics for model classes of the subject classroom system and to draw the effective plan of the system. The conclusions are as follows First, the biggest advantage of the system is to fulfill the educational goal according to an individual level and ability of each student while the biggest disadvantage is the inconvenience of students to change their classrooms for each specific class. Second, it is necessary to rearrange the classrooms according to the applied subjects from the aspect of curriculum management since the time frame is not convenient for recess. English and mathematics are required preferentially as applied subjects, however Korean (as a national language) and science are needed to be taught with level-differentiated classes, too. The ideal size of classes is most likely 20-25 students according to the result of research. Lastly, the space of environment is another requirement to secure smooth flow of students' movements and extra space for technical devices used for information research. The above analysis indicates the necessity of supplementation in space planning for further implementation of subject classroom system in secondary school.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.245-253
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• 2016

Background in a novel is most important elements with characters and events, and means time, place and situation that characters appeared. Among the background, spatial background can help conveys topic of a novel. So, it may be helpful for choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels. In case of English text, It can be recognize spatial background easily because it use upper and lower case and words used with the spatial information such as Bank, University and City. But, in case Korean text, it is difficult to recognize that spatial background because there is few information about usage of letter. In the previous studies, they use machine learning or dictionaries and rules to recognize about spatial information in text such as news and text messages. In this paper, we build a nation dictionaries that refer to information such as 'Korean history' and 'Google maps.' We Also propose a method for recognizing spatial background based on patterns of postposition in Korean sentences comparing to previous works. We are grasp using of postposition with spatial background because Korean characteristics. And we propose a method based on result of morpheme analyze and frequency in a novel text for raising accuracy about recognizing spatial background. The recognized spatial background can help readers to grasp the atmosphere of a novel and to understand the events and atmosphere through recognition of the spatial background of the scene that characters appeared.

• Annual Conference on Human and Language Technology
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• 1991.10a
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• pp.196-208
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• 1991

This study focused on the role of prefabricated speech (routines and patterns) in the L2 acquisition process. The data for this study consisted of spontaneous speech samples and various observational records of three Korean children learning English as L2 in a nursery school. The specific questions addressed here were: (1) What routines, patterns, and creative constructions did the children use? (2) What was the general trend in the three children's use of routines, patterns, and creative constructions over time? The data were collected over a period of one school year by observing the children in their school. The findings were discussed from the perspective of human information processing. This study found that prefabricated speech played a significant role in the three children's L2 acquisition. The automatic processing of prefabricated speech appeared to enable the children to reduce the burden on their information processing systems, which allowed the saved resources available for other language development activities. Also, the children's language development was evident in their increase in the use of patterns. The children were moving from heavy dependence on wholly unanalyzed routines to increased use of partly unanalyzed patterns. This increased control was the result of an increase in procedural knowledge.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.19-21
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• 2010

컴퓨터 성능의 급속한 발전으로 언어 학습에 컴퓨터를 이용하려는 시도는 이제 새로운 언어 교수법 차원으로 발전하는 실정이다. 이에 따라 컴퓨터를 이용한 학습이 더욱 강조되면서, 많은 학습 프로그램이 개발되고 있다. 그러나, 기존 영어 단어 학습 시스템은 학습자에게 지나치게 많은 단어들을 단순한 방법을 통해서 학습하게 함으로써 심리적 부담을 주고 있다. 심리언어학에서는 언어 이해의 과정이 단순히 제시된 것을 그대로 받아들이는 수용의 과정이 아니라 학습자가 이미 보유한 경험과 개념을 근거로 활성망의 확산을 통해 적절한 관계를 찾는 역동적 능동적 과정이라는 이론이 있다. 본 논문에서는 언어 학습 이론을 바탕으로 단어들 사이의 관계를 부각시킴으로써 추론과 기억에 도움을 주는 영어 단어 학습 시스템을 제안한다. 본 시스템은 단어들 간의 관계를 정의한 단어 관계 망을 중심으로 단어 학습 순서를 결정할 수 있고, 이미지 및 게임 기능을 지원하여 단어학습의 흥미를 유발하는 특징이 있다.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.178-178
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• 1999

Most stochastic taggers can not resolve some morphological ambiguities that can be resolved only by referring to lexical contexts because they use only contextual probabilities based ontag n-grams and lexical probabilities. Existing lexical rules are effective for resolving such ambiguitiesbecause they can refer to lexical contexts. However, they have two limitations. One is that humanexperts tend to make erroneous rules because they are deterministic rules. Another is that it is hardand time-consuming to acquire rules because they should be manually acquired. In this paper, wepropose context-dependent lexical rules, which are lexical rules based on the statistics of a taggedcorpus, and an ambiguity-driven teaming method, which is the method of automatically acquiring theproposed rules from a tagged corpus. By using the proposed rules, the proposed tagger can partiallyannotate an unseen corpus with high accuracy because it is a kind of memorizing tagger that canannotate a training corpus with 100% accuracy. So, the proposed tagger is useful to improve theaccuracy of a stochastic tagger. And also, it is effectively used for detecting and correcting taggingerrors in a manually tagged corpus. Moreover, the experimental results show that the proposed methodis also effective for English part-of-speech tagging.

• Journal of Information Technology Applications and Management
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• v.12 no.2
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• pp.15-27
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• 2005

Text categorization systems generally use single words (unigrams) as features. A deceptively simple algorithm for improving text categorization is investigated here, an idea previously shown not to work. It is to identify useful word pairs (bigrams) made up of adjacent unigrams. The bigrams it found, while small in numbers, can substantially raise the quality of feature sets. The algorithm was tested on two pre-classified datasets, Reuters-21578 for English and Korea-web for Korean. The results show that the algorithm was successful in extracting high quality bigrams and increased the quality of overall features. To find out the role of bigrams, we trained the Na$\"{i}$ve Bayes classifiers using both unigrams and bigrams as features. The results show that recall values were higher than those of unigrams alone. Break-even points and F1 values improved in most documents, especially when documents were classified along the large classes. In Reuters-21578 break-even points increased by 2.1%, with the highest at 18.8%, and F1 improved by 1.5%, with the highest at 3.2%. In Korea-web break-even points increased by 1.0%, with the highest at 4.5%, and F1 improved by 0.4%, with the highest at 4.2%. We can conclude that text classification using unigrams and bigrams together is more efficient than using only unigrams.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.477-483
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• 2011

These days, smart phones are being widely used and accordingly, a larger number of consumers have become interested in them, thus many applications are being developed with a variety of forms. There are various fields in it, such as multimedia, games, information and education, as per users' disposition and characteristics. As for the current contents for language education in mobile environment, the market is dominated by contents for learning foreign language such as English, Japanese and Chinese, while contents for educating Korean language are minuscule. In this paper, thus, we design and implement a elementary Korean language educational contents for foreign beginners who can use the contents at their smart phones with Android OS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.953-955
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• 2010

Most domestic educational mobile contents put special stress on learning foreign languages such as English, and usually the telecommunications companies and the education companies partner to provide mobile terminals with the contents such as video files. Recently the trend of mobile platforms for the educational contents have been changed because of the release the many kinds of smart phones like iPhone and Google Phone. In this paper, we design the educational contents for Korean listening education to aid to study Korean effectively as a foreign language. It carries out a detailed design to realize and run the contents based on the Android OS which is an open source platform backed by Google.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1977-1985
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• 2007

The character recognition technique is one of the artificial intelligence and has been widely applied in the automated system robot HCI(Human Computer Interaction), etc. This paper introduces the character set and the representative character that can be used in the recognition of the mage ROI. The character codes in this ROI include the digit, symbol, English and Hereat etc. We proposed the efficient multi-classifier structure by combining the small-size classifiers hierarchically. Moreover, we generated each small-size classifiers by delta-bar-delta learning algorithm. We tested the performance with various kinds of images and achieved the accuracy of 99%. The proposed multi-classifier showed the efficiency and the reliability for the mixed character code set.

• Journal of Korean language education
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• v.28 no.2
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• pp.1-36
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• 2017

This study investigated the correlation between learners' psychological and social factors and their syntactic complexity of speaking. The study collected samples of Korean spoken production of 61 learners with English, Chinese, Japanese and other L1 backgrounds and applied mini-TOPIK, mini-AMTB, and SASIQ for 70 minutes. The study found that: (i) integrative motivation showed positive correlation with a number of simple complex clauses, but instrumental motivation correlated negatively with a number of adverbial clauses, indicating that high motivation hindered producing highly complex clauses although it triggered producing simple complex clauses, (ii) social contact with L2 native speakers showed positive correlation with general L2 development and a number of simple complex clauses, but revealed negative correlation with double or triple complex clauses, (iii) hours of L2 listening showed very strong positive correlation with producing triple complex clauses and general proficiency, but indicated negative correlation with a number of simple complex clauses. The study reported that high motivation toward Korean learning and active social activities with Korean native speakers helped produce simple complex clauses while hours of listening to Korean helped produce triple complex clauses.