• 한국치위생학회지
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• 제23권6호
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• pp.451-458
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• 2023

Objectives: The purpose of this study is to explore the research trends of elderly oral health through a language network analysis. Methods: A total of 354 published studies with 668 keywords were collected from the Research Information Sharing Service (RISS) between 2000 and 2022. Language network analysis was performed using Textom 6.0, Ucinet 6.774, and NetDraw 2.183. Results: The most frequent keywords were 'elderly', 'oral health', 'quality of life', and 'OHIP-14'. The result of frequency-inverse document frequent keywords showed similar results to the most frequent keywords. The N-gram of keywords shows that 'elderly', 'oral health' (18 times) and 'elderly', 'depression' (7 times). As a results of the analysis of degree centrality and between centrality, 'elderly', 'oral health', and 'quality of life' were found to be high. The CONCOR analysis identified the main clusters of 'quality of life', 'oral health behavior', 'health', and 'oral function disorder'. Conclusions: The results of the current study could be available to know research trends in elderly oral health and it is necessary to improve more comprehensive study in follow-up study.

• Journal of Information Technology Applications and Management
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• 제30권4호
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• pp.77-86
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• 2023

This study conducted sentiment analysis on Hong Kong cinema from two distinct eras, pre-2000 and post-2000, examining audience preferences by comparing keywords from movie reviews. Before 2000, positive keywords like 'actors,' 'performance,' and 'atmosphere' revealed the importance of actors' popularity and their performances, while negative keywords such as 'forced' and 'violence' pointed out narrative issues. In contrast, post-2000 cinema emphasized keywords like 'scale,' 'drama,' and 'Yang Yang,' highlighting production scale and engaging narratives as key factors. Negative keywords included 'story,' 'cheesy,' 'acting,' and 'budget,' indicating challenges in storytelling and content quality. Word2Vec analysis further highlighted differences in acting quality and emotional engagement. Pre-2000 cinema focused on 'elegance' and 'excellence' in acting, while post-2000 cinema leaned towards 'tediousness' and 'awkwardness.' In summary, this research underscores the importance of actors, storytelling, and audience empathy in Hong Kong cinema's success. The industry has evolved, with a shift from actors to production quality. These findings have implications for the broader Chinese film industry, emphasizing the need for engaging narratives and quality acting to thrive in evolving cinematic landscapes.

• International Journal of Advanced Culture Technology
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• 제12권1호
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• pp.270-275
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• 2024

Introduction. In this study, purpose is to analize the types of golf tourism, inbound or outbound, by using big data and see how movement of industry is being changed and what changes have been made during and after Covid-19 in golf industry. Method Using Textom, a big data analysis tool, "golf tourism" and "Covid-19" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 1 st January, 2023 to 31st December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "golf tourism" was removed through the refining process, and similar keywords were grouped into the same keyword to perform analysis. As a result of the word refining process, top 36 keywords with the highest relevance and search frequency were selected and applied to this study. The top 36 keywords derived through word purification were subjected to TF-IDF analysis, visualization analysis using Ucinet6 and NetDraw programs, network analysis between keywords, and cluster analysis between each keyword through Concor analysis. Results By using big data analysis, it was found out option of oversea golf tourism is affecting on inbound golf travel. "Golf", "Tourism", "Vietnam", "Thailand" showed high frequencies, which proves that oversea golf tour is now the re-coming trends.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.270-273
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• 2001

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce management. For allowing intelligence, we used fuzzy theory. Fuzzy theory is very useful method where keywords have vague conditions and system must process that conditions. So, using theory, we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.285-289
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• 2009

태그는 콘텐츠를 대표하는 신뢰도가 높은 키워드이다. 하지만 일부 기업과 사람들이 콘텐츠와 관련이 없는 키워드를 태그로 사용하여 본 논문에서는 무분별하게 사용된 키워드를 정련하는 알고리듬을 제안한다. 키워드 정련과 관련된 연구는 진행되지 않았지만, 본 논문에서는 단어와 단어사이에 가상의 링크를 생성, TextRank 알고리듬을 적용하여 콘텐츠에서 단어의 중요도를 계산하여 중요도가 낮은 단어의 일부를 콘텐츠의 제작자가 작성한 키워드에서 제거하여 키워드 정련을 하였다. 그 결과, 단순히 단어의 중요도가 낮은 하위 n%의 단어를 제거하는 방법보다는 신뢰도 구간을 만족할 때까지 제거하는 방법이 훨씬 좋은 키워드 정련 결과를 보였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.99-100
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• 2018

Citation of academic research papers is a very important result for academic researchers, and their utilization is becoming an important evaluation factor. Most papers are composed of authors' keywords. However, there may be some papers with little relevance between the textual content and the presented keywords. Therefore, it is necessary to extract and present important keywords through objective methods for titles and abstracts of theses. In this paper, we present the development results of important keywords through data visualization for academic research papers.

• 대한한의정보학회지
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• 제11권1호
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• pp.74-82
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• 2005

Objective We wish that oriental medicine theses can now be searched for by computer. So we have studied thesaurus and keywords in OMIS(Oriental Medicine Information System) Methodologies We have compared the keyword with the Thesaurus in the OMIS. So We have analyzed those into the agreement rate and the disagreement rate. Repeatedly, we have analyzed the agreement rate and the disagreement rate in chronological order. Conclusions 1. As the most of authors don't know about thesaurus, So many keywords disagree with thesaurus. 2. Because thesaurus system is very difficult to general authors. So system administors must build synonym data base, if many authors easily use thesaurus system. 3. We have to require institute editor to modify editorial policy. Presently most of institute require only one foreign language keywords, but it must be required foreign and Korean language keywords. 4. We must study not only oriental medicine thesaurus but also the other science thesaurus.

• 디지털산업정보학회논문지
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• 제16권3호
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• pp.25-36
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• 2020

Topics calculated using LDA topic modeling have to be labeled separately. When labeling a topic, we look at the words that represent the topic, and label the topic. Therefore, it is important to first make a good set of words that represent the topic. This paper proposes a method of calculating a set of words representing a topic using TextRank, which extracts the keywords of a document. The proposed method uses Relevance to select words related to the topic with discrimination. It extracts topic keywords using the TextRank algorithm and connects keywords with a high frequency of simultaneous occurrence to express the topic with a higher coverage.

• 한국디지털건축인테리어학회논문집
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• 제12권2호
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• pp.53-60
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• 2012

In this paper, we present new methods for identifying keywords for foresight topics that utilize the internet and textmining techniques to draw objective and quantified information that support experts' qualitative opinions and evaluations in foresight. Furthermore, by applying this fabricated procedure, we have derived keywords to analyze priorities in architectural engineering. Not much difference between qualitative methods of experts and quantitative methods such as text mining has been observed from comparison between technologies derived via qualitative method from "The Science Technology Vision" (control group). Therefore, as a quantitative tool useful for drawing keywords for foresight, textmining can supplement quantitative analysis by experts. In addition, depending on the level and type of raw data, text mining can bring better results in deriving foresight keywords. For this reason, research activities accommodating Internet search results and the development of textmining methods for analyzing current trends are in demand.

• International Journal of Internet, Broadcasting and Communication
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• 제14권4호
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• pp.52-57
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• 2022

In this study, keywords from representative online portal sites such as Naver, Google, and Youtube were collected based on text mining analysis technique using Textom to check the changes in metqaverse after COVID-19. before Corona, it was confirmed that social media platforms such as Kakao Talk, Facebook, and Twitter were mentioned, and among the four metaverse, consumer awareness was still concentrated in the field of life logging. However, after Corona, keywords from Roblox, Fortnite, and Geppetto appeared, and keywords such as Universe, Space, Meta, and the world appeared, so Metaverse was recognized as a virtual world. As a result, it was confirmed that consumer perception changed from the life logging of Metaverse to the mirror world. Third, keywords such as cryptocurrency, cryptocurrency, coin, and exchange appeared before Corona, and the word frequency ranking for blockchain, which is an underlying technology, was high, but after Corona, the word frequency ranking fell significantly as mentioned above.