• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.296-303
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• 2020

The purpose of this study was to examine the keywords of studies related to young children's play in the selected registered and candidate academic journals and the network of the keywords by conducting a semantic network analysis. The selected journals were published over the past decade in diverse fields of study that included social sciences and life sciences such as education and early childhood education. The findings of the study were as follows: First, there was a great increase in the studies related to early childhood play over the last five years in comparison with the first term(2009-2013). As a result of analyzing how many studies were included in the journals by field, the largest numbers of the studies were published in the field of education, followed by early childhood education, and life sciences. Second, when the network of the keywords was analyzed, the major keywords in the first term were playfulness, role play, young children, creativity, play, and peer play interaction. In the second term(2014-2018), playfulness was also the most frequently exhibited keyword, followed by young children, play, and peer play behavior. Keywords such as teacher-child interaction, language skills, happiness, cognitive ability, early childhood education newly appeared.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.263-287
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• 2021

Researches on inequality in Korean society has been sporadically conducted in various areas. In this study, research trend related to inequality was analyzed through basic statistical analysis, co-occurrence analysis, and main path analysis using articles related to inequality from Korea citation index. In basic statistical analysis, key authors, journals, and articles are identified. In co-occurrence analysis, income inequality, educational inequality, welfare inequality, and policy on inequality were identified as main topics. Main path analysis showed two research trends after 2004. One was research trend on economic inequality, and the other was on health inequality and social structural inequality.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.495-501
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• 2013

The words a speaker uses can be regarded as the core, the main issue and a symbolic icon of what he says. Applying this to presidents' addresses of each English literary society in Korea shows that frequency in use and the linkage of words they use in their addresses are value and ideas executive officers pursue. The purpose of this study is to analyze the contents of presidents' addresses introduced in home page of each English literary society in Korea and investigate features and constitution of them each, focusing on analysis of a language network. The results of this study show the features of resemblances and differences of commonly-used words. In addition, these results appear to suggest that they can be also applied to a comparative study between the English literary societies in Korea.

• Journal of KIISE
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• v.44 no.12
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• pp.1313-1318
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• 2017

Aggregating local features in a single vector is a fundamental problem in an image search. In this process, the image search process can be speeded up if binary features which are extracted almost two order of magnitude faster than gradient-based features are utilized. However, in order to utilize the binary features in an image search, it is necessary to study the techniques for clustering binary features to generate binary visual words. This investigation is necessary because traditional clustering techniques for gradient-based features are not compatible with binary features. To this end, this paper studies the techniques for clustering binary features for the purpose of generating binary visual words. Through experiments, we analyze the trade-off between the accuracy and computational efficiency of an image search using binary features, and we then compare the proposed techniques. This research is expected to be applied to mobile applications, real-time applications, and web scale applications that require a fast image search.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.367-370
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• 2022

본 연구는 코로나19 발생 전·후 공공의료를 둘러싼 사회적 인식변화를 뉴스빅데이터를 통해 파악하고자 시도되었다. 뉴스빅데이터는 코로나19 확진자가 처음 발생한 2020년 1월을 기준으로 나누었으며, 코로나19 발생 이전(2018년 1월~2019년 12월, 총 24개월) 40,834건과 코로나19가 발병 이후(2020년 1월~2021년 12월, 총 21개월) 61,761건이었다. 수집된 빅데이터는 R 4.1.1 for Windows를 활용하여 단어 빈도 분석, 연관규칙분석을 실시하였다. 연구결과, 코로나19 발생 전후 뉴스기사에서 공공의료를 둘러싼 핵심어를 비교할 때 코로나19 발생 후에 발생 전보다 큰 폭으로 상승한 단어는 '확산'(664%), '대응'(658%), '의사'(518%), '상황'(504%), '공공병원'(486%), '의료진'(455%), '확충'(324%), '인력'(305%), '어려움'(272%), '정부'(247%)순으로 나타났다. 코로나19 발생 전후 공공의료를 둘러싼 키워드의 연관규칙 분석을 통해서 의료의 패러다임이 일자리 산업에서 감염증 대응을 위한 보건의료로 전환되는 것을 알수 있었다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.954-966
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• 2021

With regards to the marine spatial plannings of the world, the spaces are being managed through the integration of various uses and the establishment of systems and laws in the perspective of the utilization of spaces. In the perspective of policy establishment, the policy readiness level is applied to analyze the trends in the studies on South Korea's marine spatial plans. The scope of the study included analyzing marine spatial plan as a keyword in articles published over the period from 2010 to 2020. The methods of analysis included the analyses of the frequency of word appearance, word clouds, and appearance intensity, which were used to identify key issues. Five keywords that were related to the topics were identified, and were again used to identify the key themes. The core themes were changing in all phases, such as the principles development phase, institutionalization phase, policy verification phase. For future benefit, this requires more research in South Korean public organizations and universities.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2133-2138
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• 2017

The analysis of existing XML documents and other documents was centered on words. It can be implemented using a morpheme analyzer, but it can classify many words in the document and cannot grasp the core contents of the document. In order for a user to efficiently understand a document, a paragraph containing a main word must be extracted and presented to the user. The proposed system retrieves keyword in the normalized XML document. Then, the user extracts the paragraphs containing the keyword inputted for searching and displays them to the user. In addition, the frequency and weight of the keyword used in the search are informed to the user, and the order of the extracted paragraphs and the redundancy elimination function are minimized so that the user can understand the document. The proposed system can minimize the time and effort required to understand the document by allowing the user to understand the document without reading the whole document.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.207-214
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• 2012

The purpose of this study was to review the agreement and disagreement logics on privatization of health care to bring quality enhancement of medical service and alienated area without medical services at the same time, to identify the core keywords through language network analysis a kind of contents analysis on the editorials dealing with privatization of health care and hospitals for profit published on the major daily newspapers for the recent three years, and to find out what is the core of the controversy through the connection centrality analysis of core keywords. Conclusively, it was found from the centrality analysis that "medical service," "hospital," "privatization," "privatization of health care," "hospital for profit" and "Government" were situated in the center of the controversy. It is natural that keywords such as "medical service," "hospital," "privatization," "privatization of health care"and "hospital for profit" were located in the center because this study reviewed the editorials published on major newspapers for the recent three years regarding the privatization of health care or hospital for profit. Next important keywords (words) were "people," "health"and "health insurance." It shows that privatization of health care was not simply seen as the opening of medical service market but as an important issue related to health of people and health Insurance. Next words with high centrality were "objection" and "allowance." Through the contents analysis of editorials for the last three years, it was found that the opinions for and against the privatization were equally matched according to the centrality analysis result. On the other hand, there is one noticeable result in centrality analysis, which is the keywords such as "US," "Korea US" and "FTA" showed centrality to some extent. It shows privatization is handled relating US and Korea US FTA by editorials.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.317-320
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• 2017

개체명 인식은 자연어 문장에서 장소, 제작물, 사람 등 분류를 통한 의미 부여가 가능한 단어를 파악하는 기술로서 의미 분석을 위한 핵심 기술이다. 현재 많은 개체명 분석 관련 연구들은 형태소 분석 결과에 의존적인 형태를 갖고 있어서, 형태소 분석 결과의 정확성이 개체명 분석 결과의 성능에 영향을 미치고 있다. 본 연구에서는 형태소 분석 과정을 거치지 않는 음절 기반의 개체명 분석 기술을 제안하여 형태소 분석의 정확도가 낮은 통신어, 신조어 분석 성능을 향상하였다. 또한, 자동화된 방법으로 음절 단위 개체명 말뭉치 및 개체명 사전을 구축하는 프로세스를 정의하여 개체명 분석의 정확도 향상 및 인지 범주의 확대를 도모하였다. 본 연구에서 제안한 개체명 인식 기술은 한국어 개체명 표준에 기반한 129가지의 개체명 분류가 가능하며, 이는 자연어 처리 기술이 필요한 산업계에서 상용화하는데 큰 기여를 할 것으로 판단된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3677-3688
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• 2011

The patent information retrieval system can serve a variety of purposes. In general, the patent information is retrieved using limited key words. To identify earlier technology and priority rights repeated effort is needed. This study proposes a method of content-based retrieval using text mining. Using the proposed algorithm, each of the documents is invested with characteristic value. The characteristic values are used to compare similarities between query documents and database documents. Text analysis is composed of 3 steps: stop-word, keyword analysis and weighted value calculation. In the test results, the general retrieval and the proposed algorithm were compared by using accuracy measurements. As the study arranges the result documents as similarities of the query documents, the surfer can improve the efficiency by reviewing the similar documents first. Also because of being able to input the full-text of patent documents, the users unacquainted with surfing can use it easily and quickly. It can reduce the amount of displayed missing data through the use of content based retrieval instead of keyword based retrieval for extending the scope of the search.