• Title/Summary/Keyword: 주제어

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Key Word Network Analysis to Identify the Trends of Research in Social Welfare for Disabled People (장애인복지연구의 동향에 관한 주제어 연결망 분석)

  • Kam, Jeong Ki;Oh, Bong Hee
    • 재활복지
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    • v.21 no.1
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    • pp.1-26
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    • 2017
  • The main purpose of this paper is identifying the trends of researches in the realm of social welfare for disabled people. It tries to introduce an alternative analytic approach - key word network analysis - that might surpass the shortage of analysis methods of existing studies which have mainly relied on descriptive analysis. For this purpose the authors constructed a database composed of key words and informations about research methods of the data sources of this study. The sources are such researches as doctoral theses and the papers of Korean Journal of Social Welfare and Journal of Rehabilitation Research which were published during the 20 years from 1996 to 2015. Total numbers of the thesis or papers analysed at this study are 1,034. The results are shown in three ways as follows: First, the method trends of selected researches. Second the lists of interested types and population groups of the disabled persons and interested issues. Third, the intellectual structure of the research. Based on the findings of this study, some suggestions are given considering desirable directions of future researches in relation to perspectives, methods, targets and subjects of them.

A Social Network Analysis on the Research Trend of Korean Rural Development (농촌개발 연구동향에 관한 사회연결망분석 - 주제어 중심 구조분석을 중심으로 -)

  • Park, Soo-Jin;Na, Ju-Mong
    • Journal of the Korean Regional Science Association
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    • v.32 no.3
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    • pp.29-43
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    • 2016
  • The purpose of this study is to derive research subject that has been overlooked in previous studies and contribute to seek to the direction of research in rural development by analyzing the studies in the last 30 years on rural society. In this study, Social Network Analysis was used for identifying the changes in research themes and connection structure of keyword. The study shows that in the previous Roh Moo-Hyun's Administration from 1986 to 2000, the convergence of the research is not active. In terms of the connection structure of keyword, lots of keywords are connected to the 'Migration, IMF, Satisfaction, Green Tourism' but its form is not complicated. In the Roh Moo-Hyun's Administration from 2001 to 2007, the academic exchanges and convergence of keywords on rural development were promoted research. The connection structure of keyword was formed like a complex cluster associated with 'The Rural Elderly, Rural Tourism, Rural Development Policy, Urban-Rural Comparison'. Although some scholars who study 'Women's Studies, Tourism' formed the cluster, its form is still passive. Since 2008 until now, the keyword network of rural development research clustered densely and formed singly. It reveals that the convergence of research subjects has proceeded actively. And studies such as the 'Community, Participation, Social capital, Quality of life, Social networks, Alternative food movement' have begun.

Mobile Device and Virtual Storage-Based Approach to Automatically and Pervasively Acquire Knowledge in Dialogues (모바일 기기와 가상 스토리지 기술을 적용한 자동적 및 편재적 음성형 지식 획득)

  • Yoo, Kee-Dong
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.1-17
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    • 2012
  • The Smartphone, one of essential mobile devices widely used recently, can be very effectively applied to capture knowledge on the spot by jointly applying the pervasive functionality of cloud computing. The process of knowledge capturing can be also effectively automated if the topic of knowledge is automatically identified. Therefore, this paper suggests an interdisciplinary approach to automatically acquire knowledge on the spot by combining technologies of text mining-based topic identification and cloud computing-based Smartphone. The Smartphone is used not only as the recorder to record knowledge possessor's dialogue which plays the role of the knowledge source, but also as the sensor to collect knowledge possessor's context data which characterize specific situations surrounding him or her. The support vector machine, one of well-known outperforming text mining algorithms, is applied to extract the topic of knowledge. By relating the topic and context data, a business rule can be formulated, and by aggregating the rule, the topic, context data, and the dictated dialogue, a set of knowledge is automatically acquired.

Development of Similar Bibliographic Retrieval System based on Neighboring Words and Keyword Topic Information (인접한 단어와 키워드 주제어 정보에 기반한 유사 문헌 검색 시스템 개발)

  • Kim, Kwang-Young;Kwak, Seung-Jin
    • Journal of Korean Library and Information Science Society
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    • v.40 no.3
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    • pp.367-387
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    • 2009
  • The similar bibliographic retrieval system follows whether it selects a thing of the extracted index term and or not the difference in which the similar document retrieval system There be many in the search result is generated. In this research, the method minimally making the error of the selection of the extracted candidate index term is provided In this research, the word information in which it is adjacent by using candidate index terms extracted from the similar literature and the keyword topic information were used. And by using the related author information and the reranking method of the search result, the similar bibliographic system in which an accuracy is high was developed. In this paper, we conducted experiments for similar bibliographic retrieval system on a collection of Korean journal articles of science and technology arena. The performance of similar bibliographic retrieval system was proved through an experiment and user evaluation.

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Graph Learning System for Analyzing Bias among News Using Keyword Distance Model (주제어 문장거리를 이용한 뉴스 편향성 분석 그래프 학습)

  • Cho Chanwoo;Cho Chanhyung
    • Annual Conference on Human and Language Technology
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    • 2023.10a
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    • pp.533-538
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    • 2023
  • 문서에서 저자의 의도와 주제, 그 안에 포함된 감성을 분석하는 것은 자연어 연구의 핵심적인 주제이다. 이와 유사하게 특정 글에 포함된 정치적 문화적 편향을 분석하는 것 역시 매우 의미 있는 연구주제이다. 우리는 최근 발생한 한 사건에 대하여 여러 신문사와 해당 신문사에서 생산한 기사를 중심으로 해당 글의 정치적 편향을 정량화 하는 방법을 제시한다. 그 방법은 선택된 주제어들의 문장 공간에서의 거리를 중심으로 그래프를 생성하고, 생성된 그래프의 기계학습을 통하여 편향과 특징을 분석하였다. 그리고 그 그래프들의 시간적 변화를 추적하여 특정 신문사에서 특정 사건에 대한 입장이 시간적으로 어떻게 변화하였는지를 동적으로 보여주는 그래프 애니메이션 시스템을 개발하였다. 실험을 위하여 최근 이슈에 대하여 12개의 신문사에서 약 2000여 개의 기사를 수집하였다. 그 결과, 약 82%의 정확도로 일반적으로 알려진 정치적 편향을 예측할 수 있었다. 또한, 학습 데이터에 쓰이지 않은 신문기사를 활용하여도 같은 정도의 정확도를 보임을 알 수 있었다. 우리는 이를 통하여 신문기사에서의 정치적 편향은 작성자나 신문사의 특성이 아니라 주제어들의 문장 공간에서의 거리 관계로 특성화할 수 있음을 보였다. 할 수 있다.

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A Study on the Indexing Editorial Cartoons (신문만화 색인에 관한 연구)

  • 이지영;이나니
    • Proceedings of the Korean Society for Information Management Conference
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    • 1998.08a
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    • pp.215-218
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    • 1998
  • 신문만화는 신문에 실린 기사중 가장 핵심적인 내용을 간략한 그림으로 함축하여 정보를 전달한다. 그러나 만화의 함축성과 비유, 짤막한 텍스트 때문에 객관적인 색인어의 추출이 어려운 것이 사실이다. 본 연구에서는 신문만화에서 키워드를 추출하기 위하여 만화의 내용과 관련이 있는 신문기사에서 색인어를 추출하는 방안에 대해 논하였다. 연구에서는 조선일보에 게재된 한컷만화과 네컷만화를 각 1점씩 예로 들어 비주제색인어와 주제색인어를 부여하였다. 특히 주제색인어는 내용상의 연관성이 있는 신문기사를 선정하여 추출하였다.

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Exploration of Intellectual Structure of Artificial Intelligence Field Using Co-word Analysis (동시출현 단어 분석을 통한 지식 구조의 파악 : 인공지능 분야를 대상으로)

  • 이미경;정영미
    • Proceedings of the Korean Society for Information Management Conference
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    • 2003.08a
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    • pp.245-251
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    • 2003
  • 이 연구에서는 통제된 색인어를 이용하여 파악한 지식 구조와 통제되지 않은 키워드를 이용한 지식 구조를 비교하여 두 구조가 어떤 차이점을 보이는지를 살펴보았다. 또한 색인효과가 어떻게 나타나는지, 비통제어를 사용한 경우가 실제적으로 더 상세한 하위 영역을 표현하는지를 확인하고자 하였다. 실험 결과 통제된 색인어인 주제명표목을 사용한 영역지도와 비통제 색인어인 키워드를 사용한 영역지도 둘 다 인공지능 분야의 주요 분야들을 비슷하게 나타냈지만, 주제명표목을 사용한 경우에 색인효과가 일부 나타났다. 그리고 대체적으로 주제명표목에 기반한 영역지도보다는 키워드에 기반한 영역지도가 더 상세하게 나타났다.

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Application of a Naive Bayes Classifier for Topic Word Sense Disambiguation (주제어의 중의성 해소를 위한 Naive Bayes 분류기 적용에 관한 연구)

  • 유현숙;정영미
    • Proceedings of the Korean Society for Information Management Conference
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    • 2000.08a
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    • pp.71-74
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    • 2000
  • 단어의 의미 중의성을 해소하는 것은 자연언어처리의 중요한 문제 중의 하나이다. 특히 문서의 주제어가 중의성을 가질 때, 이 문서는 부적합한 범주에 속하게 되어 정보검색시 잡음을 일으키는 원인이 되기도 한다. 그러므로, 본 논문에서는 문서를 대표하는 주재어의 의미 중의성을 해소하기 위해 주변 문맥자질을 고려하는 방법을 모색한다 이를 위해 자연언어처리의 통계적 방법으로 문서 범주화에 많이 사용되는 Naive Bayes 분류기를 중의성 해소에 적용하고, 그 결과 얻어진 중의성 해소 성능을 평가한다.

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A Bibliometric Study on the KCI Listed Theological Journals (KCI 등재 신학 학술지에 대한 계량서지학적 분석)

  • Yoo, Yeong Jun;Lee, Jae Yun
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.31 no.3
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    • pp.5-27
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    • 2020
  • This study aimed at analyzing the keywords and authors of the KCI listed theological journals and finding the official research performance of Korean theology. This study divided the periods in two according to how duplicate the authors are and found hierarchical clusters by analyzing 92 keywords using the McQuitty method. In analyzing them, the Ward linkage method was selected to prevent the authors from gathering into a small number of clusters. Also, to find how influential the journals were to the keywords, the keywords and the percentage of the journals in them were presented together. The authors were analyzed in terms of deciding the positions of them using normalized performance index representing the number of journals and growth index as a growth tendency. Especially, significant researchers were all reformed theologians in a growth index. In the analysis of the keywords of the KCI journals and the authors, the main subject terms of the Korean theology were related to systematic theology and the New Testament. By analyzing the KCI listed journals as the Korean official citation index, this study has made a difference to the advanced articles analyzing the non-KCI listed theological journals.

A Sentence Theme Allocation Scheme based on Head Driven Patterns in Encyclopedia Domain (백과사전 영역에서 중심어주도패턴에 기반한 문장주제 할당 기법)

  • Kang Bo-Young;Myaeng Sung-Hyon
    • Journal of KIISE:Software and Applications
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    • v.32 no.5
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    • pp.396-405
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    • 2005
  • Since sentences are the basic propositional units of text, their themes would be helpful for various tasks that require knowledge about the semantic content of text. Despite the importance of determining the theme of a sentence, however, few studies have investigated the problem of automatically assigning the theme to a sentence. Therefore, we propose a sentence theme allocation scheme based on the head-driven patterns of sentences in encyclopedia. In a serious of experiments using Dusan Dong-A encyclopedia, the proposed method outperformed the baseline of the theme allocation performance. The head-driven pattern 4, which is reconfigured based on the predicate, showed superior performance in the theme allocation with the average F-score of $98.96\%$ for the training data, and $88.57\%$ for the test data.