• 한국초등과학교육학회지:초등과학교육
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• 제29권2호
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• pp.134-143
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• 2010

The purpose of this study is to devise a new method for examining the readabilities of textbooks and to compare the readabilities of elementary school science textbooks. Third and sixth grade science textbooks were compared in terms of word, sentence, and paragraph in this study. In the word analyses, criterion suggested by Kim (2003) who classified about 238,000 words into seven categories according to their educational importances was adopted. In this study, the words from 3rd and 6th grade science textbooks were classified into four categories, and then the kinds and frequencies of words in each category were investigated. In the sentence analyses, sentences were classified either a simple sentence or a compound/complex sentence, and the ratios of each type were calculated. The average number of words in a sentence was also calculated in the sentence analyses. The ratios of conjunctions and demonstratives were examined in the paragraph analyses. The results indicated that both the kinds and frequencies of words in 3rd grade science textbook were smaller than those of 6th grade one. However, both science textbooks were similar in the distributions of words across the four categories. The ratio of simple sentences in 3rd grade science textbook was higher than that of 6th grade one, and the length of a sentence in 3rd grade science textbook was also shorter than that of 6th grade one. Both the ratios of conjunctions and demonstratives in 3rd grade science textbook were lower than those of 6th grade one.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 2002년도 Language, Information, and Computation Proceedings of The 16th Pacific Asia Conference
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• pp.79-91
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• 2002

Structural analysis of compound words is necessary and an important process in natural language processing. Proposed here is a corpus- and statistics- based method for the structural analysis of compound words in Japanese. We determine the structure of a compound word by using Internet corpus and calculating the strength of word association among its constituent words. Experiments with 5, 6, 7, and 8 kanji compound words show that our method works well and its performance is better than those of other comparable studies.

• 한국컴퓨터정보학회논문지
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• 제23권10호
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• pp.173-180
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• 2018

In this paper, we analyzed key keywords and research themes in the field of defense research using keyword network analysis and tried to grasp the whole knowledge structure. To do this, we extracted data from 2,165 research data from defense related research institutes from 2010 to 2017 and applied the Pareto rule to the number of abstracts of words and the number of links between words, We extracted a total of 2,303 words based on the criterion and extracted 204 final key words through component analysis. By analyzing the centrality and cohesiveness through these key words, we confirmed the concept of core research in the defense field and derived a total of 7 large groups and 16 small groups of each group in the knowledge structure of the defense area.

• Journal of Information Processing Systems
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• 제18권3호
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• pp.344-358
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• 2022

Text summarization is the task of producing a shorter version of a long document while accurately preserving the main contents of the original text. Abstractive summarization generates novel words and phrases using a language generation method through text transformation and prior-embedded word information. However, newly coined words or out-of-vocabulary words decrease the performance of automatic summarization because they are not pre-trained in the machine learning process. In this study, we demonstrated an improvement in summarization quality through the contextualized embedding of BERT with out-of-vocabulary masking. In addition, explicitly providing precise pointing and an optional copy instruction along with BERT embedding, we achieved an increased accuracy than the baseline model. The recall-based word-generation metric ROUGE-1 score was 55.11 and the word-order-based ROUGE-L score was 39.65.

• 대한안전경영과학회지
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• 제14권3호
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• pp.221-227
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• 2012

This research is a key words analysis on Radio Frequency Identification. Key words were collected from Korean research papers in the electronic library DBpia. 700 papers published from 2001 to 2011 were included. The number of collected key words is 1460. The trend of publishing research papers was increased rapidly from 2005, reached peak at 2009 and decreased after 2010. Majority of key words were related to hardware, information technology and standardization. Selected 128 key words were analyzed and clustered by social network analysis to find a relationship among key words on RFID.

• 인지과학
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• 제35권2호
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• pp.97-112
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• 2024

한글에서 글자는 단어를 구성하는 주요한 단위이다. 본 연구는 한글 글자의 속성(글자의 빈도, 모음의 유형, 받침의 유무, 글자의 위치)이 단어와 비단어의 명명에 영향을 미치는지를 알아보고자 하였다. 선형혼합 효과분석 결과 단어는 첫째 글자의 빈도가 증가할수록 명명시간이 감소하였으며, 첫째 글자에 받침이 있을 때 명명시간이 감소하였다. 또한, 단어가 횡모음 유형일 때보다 종모음 유형일 때 명명 정확률이 더 높았으며 첫째 글자에 받침이 없을 때보다 있을 때 명명시간이 감소하였다. 비단어는 첫째 글자의 빈도와 둘째 글자의 빈도가 각각 증가할수록 명명시간이 감소하였으며 명명 정확률이 더 높았다. 비단어도 횡모음 유형일 때보다 종모음 유형일 때 명명 정확률이 더 높았다. 본 연구에서 둘째 글자의 빈도 효과는 단어와 비단어에 따라 달랐지만, 첫째 글자의 빈도효과와 모음 유형의 효과는 일관되게 나타났다. 시각단어재인에 대해 연구 결과의 함의를 논의하였다.

• 한국디자인학회:학술대회논문집
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• 한국디자인학회 2005년도 추계 학술발표대회 논문집
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• pp.262-263
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• 2005

• 한국식생활문화학회지
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• 제27권5호
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• pp.445-458
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• 2012

This study was conducted to approach the Korean new food words for the years 1994-2005 from the stance of food ethics. The new food words were categorized into food industry, foodstuffs, cooking, various foods, processed foods, distribution, and consumer health. The principles of food ethics applied to new food words include a respect for life, justice, environmental preservation, priority of safety, and dynamic equilibrium. Seventy percent of new food words were ethically neutral, while 30% had significant ethical meaning. There were more words with a negative ethical meaning than with a positive one. All of the principles, except respect for life, could be successfully applied to new food words. Dynamic equilibrium was the most appropriate principle for the new food words, followed by a priority for safety, justice, and environmental preservation. The results of this study implied that moderation and balance is required in our modern dietary life.

• Journal of Information Science Theory and Practice
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• 제9권1호
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• pp.24-34
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• 2021

The popularity of social networking sites (SNS) has facilitated communication between users. The usage of SNS helps users in their daily life in various ways such as sharing of opinions, keeping in touch with old friends, making new friends, and getting information. However, some users misuse SNS to belittle or hurt others using profanities, which is typical in cyberbullying incidents. Thus, in this study, we aim to identify profane words from the ASKfm corpus to analyze the profane word distribution across four different roles involved in cyberbullying based on lexicon dictionary. These four roles are: harasser, victim, bystander that assists the bully, and bystander that defends the victim. Evaluation in this study focused on occurrences of the profane word for each role from the corpus. The top 10 common words used in the corpus are also identified and represented in a graph. Results from the analysis show that these four roles used profane words in their conversation with different weightage and distribution, even though the profane words used are mostly similar. The harasser is the first ranked that used profane words in the conversation compared to other roles. The results can be further explored and considered as a potential feature in a cyberbullying detection model using a machine learning approach. Results in this work will contribute to formulate the suitable representation. It is also useful in modeling a cyberbullying detection model based on the identification of profane word distribution across different cyberbullying roles in social networks for future works.

• 한국초등과학교육학회지:초등과학교육
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• 제39권2호
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• pp.255-267
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• 2020

Students' engagement is important for meaningful learning and it has multifaceted aspects for their science learning. This study investigated elementary students' perceptions of science learning engagement. The subjects of this study were 341 4^th to 6^th elementary students. The survey questionnaires were 5-Likert scale questions and free response questions on science learning engagement. The results showed that elementary students' perceptions of behavioral engagement were higher than emotional and cognitive engagement. Keyword network analysis with NetMiner program showed that the frequent key words of science learning engagement were 'experiment', 'listening', and 'teachers' explanation', which were mostly the behavioral types of engagement. The degree centrality and eigenvector centrality of these key words appeared high. 'Interest', which is emotional engagement, were also one of the frequent key words, but the centralities of this word were relatively low. The Frequent key words of science learning disengagement were mostly related with off-tasks, not doing expected behaviors and negative emotions about science and science learning. Educational implications on science learning engagement were discussed.