• Korean Journal of Cognitive Science
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• v.2 no.2
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• pp.405-428
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• 1990

Language has a social function to communicate information. Linguists have gradually paid their attention to the function of language since the nineteen sixties, especially to the relationship of form, meaning and the function. The relationship could be more clearly grasped through disciyrse-based analysis than through sentence-based analysis. Many researches were centered on the discourse functional notion of topic. In the early 1970's the subject was defined as the grammatiocalized topic the topic as a discrete single constituent of the clause. In the late 1970's several lingusts including Givon suggerted that the topic was not an atomic, disctete entity, and that the clause could have more than one topic. The purpose of the present study is, following Givon, to study grammatical coding devices of topic and to measure the relative topic continuity/discontinuity of participant argu, ents in Korean narratives. By so doing, I would like to shed some light on effective ways of communicating information. The grammatical coding devices analyzed are the following eight structures: zero-anaphora, personal pronous, demonstrative pronouns, names, noun phrases following demonstratives, noun phrases following possessives, definite noun phrases and indefinite referentials. The narrative studied for the count was taken from the KoreanCIA chief's Testiomny:Revolution and Idol by Hyung Wook Kim. It was chosen because it was assumed that Kim's purpose in the novel was to tell a true story, which would not distort the natural use of language for literary effect. The measures taken in the analysis wre those of 'lookback', 'persistence', ambiguity'. The first of these, 'lookback', is a measure of the size of gap between the previous occurrence of a referent and its current occurence in the clause. The meausure of persistence, which is a measure of the speaker's topocal intent, reflects the topic's importance in the discourse. The third measure is a measure of ambiguity. This is necessary for assessing the disruptive effects that other topics within five previous clauses may have on topic identification. The more other topics are present within five previous clauses, the more difficult is the task of correct identification of a topic. The results of the present study show that the humanness of entities is the most powerful factior in topic continutiy in narrative discourse. The semantic roles of human arguments in narrative discourse tend to be agents or experiences. Since agents and experiences have high topicality in discourse, human entities clearly become clausal or discoursal topics. The results also show that the grammatical devices signal varying degrees of topic continuity discontinuity in continuous discourse. The more continuous a topic argument is, the less it is coded. For example, personal pronouns have the most continutiy and indefinite referentials have the least continutiy. The study strongly shows that topic continuity discontinutiy is controlled not only by grammatical devices available in the language but by socio-cultural factors and writer's intentions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1424-1440
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• 2015

It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.

• Language and Information
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• v.13 no.1
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• pp.93-125
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• 2009

We examine attributive possessive constructions in Korean in examples like wuli manwula 'my wife' and wuli nala 'my country', where an apparently plural pronoun wuli 'our' is used to convey the singular meaning of 'my.' An example like wuli manwula has been a frequent topic of joke, because it clearly contains the literal sense of 'shared wife.' This type of use and the frequent use of wuli in an exclusive my context led many to claim that these are products of Korean culture which emphasizes groups and group solidarity over individuality, the example wuli manwula being the extreme case. Drawing on the work of Taylor (1989; 1996), Croft (2001; 2003), Haspelmath (1997; 2003), and 윤재학 (2003), we compare the meanings of Korean and English possessive constructions and seek a more linguistically based account for the data. In particular, it is shown that (i) wuli in question is not really the plural form of nay 'my', (ii) the possessive constructions in Korean are more conservative and limited in possible relations than the English counterparts are, and that (iii) these two facts interact to produce the afore-mentioned uses.

• Journal of the Korean Society of Earth Science Education
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• v.9 no.1
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• pp.65-87
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• 2016

The purpose of this study is to examine Korean journals related to science education in order to analyze research trends into Nature of science in Korea. The subject of the study is the level of Korean Citation Index (KCI-listed, KCI listing candidates), that can be searched by the key phrase, "Nature of science" in Korean language through the RISS service. In this study, the Descriptive Statistical Analysis Method is utilized to discover the number of research articles, classifying them by year and by journal. Also, the Sementic Network Analysis was conducted to Word Cloud Analysis the frequency of key words, Centrality Analysis, co-occurrence and Cluster Dendrogram Analysis throughout a variety of research articles. The results show that 91 research papers were published in 25 journals from 1991 to 2015. Specifically, the 2 major journals published more than 50% of the total papers. In relation to research fields., In addition, key phrases, such as 'Analysis', 'recognition', 'lessons', 'science textbook', 'History of Science' and 'influence' are the most frequently used among the research studies. Finally, there are small language networks that appear concurrently as below: [Nature of science - high school student - recognize], [Explicit - lesson - effect], [elementary school - science textbook - analysis]. Research topic have been gradually diversified. However, many studies still put their focus on analysis and research aspects, and there have been little research on the Teaching and learning methods.

• Korean Journal of Childcare and Education
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• v.16 no.6
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• pp.253-272
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• 2020

Objective: This study aimed to analyze the counseling contents of daycare center teachers by using text mining and semantic network analysis methods to find the necessary support directions for daycare teachers and to improve the quality of child-care. Methods: Five hundred thirteen cases of counseling recorded on the open bulletin board of online counseling (Naver Bands for Nursery Teacher Counseling) were collected, and frequency analysis, centrality solidarity analysis, and machine learning-based topic analysis were conducted using the NetMiner4.3 program. Results: First, 'teacher-to-child ratio' was highest in the frequency. Second, 'colleagues' were all high in all centrality analysis. Third, machine learning-based topical analysis shows that the topics were categorized as subjects about 'childcare and education', 'working environment that supports professional development' and 'working condition', and among them, 'first-time teacher concerns' accounted for 44% of the total counseling content. Conclusion/Implications: This study implied that it is necessary to provide high-quality child-care and education to infants by lowering the 'teacher-to-child ratio', and a systematic program is needed to help improve effective communication skills in interpersonal relationships such as between parents, fellow teachers, and principals. In addition, self-development and efforts to improve teachers expertise should be prioritized in order to improve infant care quality and quality of teachers.

• Korea Trade Review
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• v.47 no.3
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• pp.177-190
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• 2022

This study is designed to identify the differences in the types and importance of trade claims at the national level. For analysis data, abstracts of arbitration and court judgments published on the website of the United Nations Commission on International Trade Law are collected and used. The target countries are China and the United States, with 102 cases from China and 59 cases from the United States. By applying topic modeling techniques to the collection decisions of China and the United States, trade claims are categorized, and the importance of each type is identified using the network centrality index derived through semantic network analysis. The analysis results are as follows. First, the main types of trade claims were the same for both the United States and China: product nonconformity, delivery issues, and payments. However, in China, the order of product nonconformity > delivery issues > payments was important, and in the United States, payments > product nonconformity > delivery issues were found to be important. This study is significant in that it presents a strategic trade claim management plan using a quantitative methodology.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.181-183
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• 2012

최근 자연어 및 정형언어 처리, 인공지능 알고리즘 등을 활용한 효율적인 의미 기반 지식모델의 생성과 분석 방법이 제시되고 있다. 이러한 의미 기반 지식모델은 효율적 의사결정트리(Decision Making Tree)와 특정 상황에 대한 체계적인 문제해결(Problem Solving) 경로 분석에 활용된다. 특히 다양한 복잡계 및 사회 연계망 분석에 있어 정적 지표 생성과 회귀 분석, 행위적 모델을 통한 추이분석, 거시예측을 지원하는 모의실험(Simulation) 모형의 기반이 된다. 본 연구에서는 이러한 의미 기반 지식모델을 통합에 있어 텍스트 마이닝을 통해 도출된 토픽(Topic) 모델 간 통합 방법과 정형적 알고리즘을 제시한다. 이를 위해 먼저, 텍스트 마이닝을 통해 도출되는 키워드 맵을 동치적 지식맵으로 변환하고 이를 의미적 지식모델로 통합하는 방법을 설명한다. 또한 키워드 맵으로부터 유의미한 토픽 맵을 투영하는 방법과 의미적 동치 모델을 유도하는 알고리즘을 제안한다. 통합된 의미 기반 지식모델은 토픽 간의 구조적 규칙과 정도 중심성, 근접 중심성, 매개 중심성 등 관계적 의미분석이 가능하며 대규모 비정형 문서의 의미 분석과 활용에 실질적인 기반 연구가 될 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.23-26
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• 2006

최근 대부분의 이러닝(E-Learning)을 교육하는 사이트는 학습 콘텐츠를 검색하는 방법이 단순한 리스트의 나열과 택스트 매칭(Text matching)방법을 사용하는 단점이 있다. 이를 보완하기 위해 좀 더 컴퓨터가 정보 데이터의 의미를 분석하여 검색이 가능하도록 개념 네트워크인 시맨틱웹(Semantic Web)이 등장하였다. 본 논문에서는 이러한 시맨틱웹의 온톨로지(Ontology) 언어 중에 토픽맵(Topic Maps)을 사용하여 많은 양의 학습 정보 데이터를 쉽고도 정확하게 연결 지어 학습 콘텐츠에 대한 정보를 표현하고, 구조화할 수 있는 방법을 모색해 보고자 한다. 학습자의 관심분야 정보, 학습객체의 학습 권장자의 정보와 함께 학습 경험과 검색 빈도수를 분석한 협력 필터링과 학습 에이전트의 개인화 기법을 동시에 사용하여 선호도를 분석한다. 이 선호도를 가지고 학습자의 메타데이터를 생성하고, 로그 데이터를 따로 데이터베이스에 저장한다. 이러한 학습자의 정보와 학습 콘텐츠간의 정보를 상호 연결하여, 그 토픽맵을 사용하여 연관관계를 정의해 줌으로써 학업성취도를 높이고, 학습자 개개인의 성향에 가장 알맞은 학습 콘텐츠를 탐색해가는 네비게이터(Navigator)를 설계하였다.

• Child Health Nursing Research
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• v.27 no.3
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• pp.201-210
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• 2021

Purpose: This study analyzed research trends related to childhood and adolescent cancer survivors (CACS) using word co-occurrence network analysis on studies registered in the Korean Citation Index (KCI). Methods: This word co-occurrence network analysis study explored major research trends by constructing a network based on relationships between keywords (semantic morphemes) in the abstracts of published articles. Research articles published in the KCI over the past 10 years were collected using the Biblio Data Collector tool included in the NetMiner Program (version 4), using "cancer survivors", "adolescent", and "child" as the main search terms. After pre-processing, analyses were conducted on centrality (degree and eigenvector), cohesion (community), and topic modeling. Results: For centrality, the top 10 keywords included "treatment", "factor", "intervention", "group", "radiotherapy", "health", "risk", "measurement", "outcome", and "quality of life". In terms of cohesion and topic analysis, three categories were identified as the major research trends: "treatment and complications", "adaptation and support needs", and "management and quality of life". Conclusion: The keywords from the three main categories reflected interdisciplinary identification. Many studies on adaptation and support needs were identified in our analysis of nursing literature. Further research on managing and evaluating the quality of life among CACS must also be conducted.

• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.3
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• pp.240-250
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• 2021

Purpose: The aim of this study is to analyze the research trends of articles on just graduated Korean nurses during the past 10 years for exploring strategies for clinical adaptation. Methods: The topics of new graduate nurses were extracted from 110 articles that have been published in Korean journals between January 2010 and July 2020. Abstracts were retrieved from 4 databases (DBpia, RISS, KISS and Google scholar). Keywords were extracted from the abstracts and cleaned using semantic morphemes. Network analysis and topic modeling were performed using the NetMiner program. Results: The core keywords included 'education', 'training', 'program', 'skill', 'care', 'performance', and 'satisfaction'. In recent articles on new graduate nurses, three major topics were extracted by Latent Dirichlet Allocation (LDA) techniques: 'turnover', 'adaptation', 'education'. Conclusion: Previous articles focused on exploring the factors related to the adaptation and turnover intentions of new graduate nurses. It is necessary to conduct further research focused on various interventions at the individual, task, and organizational levels to improve the retention of new graduate nurses.