• Journal of the Korean Dietetic Association
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• v.23 no.2
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• pp.192-201
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• 2017

This study compared the Center for Children's Foodservice Management in 2012, 2014, and 2016 using big data and opinion mining. The data on the Center for Children's Foodservice Management were collected from the portal site, Naver, from January 1 to December 31 in 2012, 2014, & 2016 and analyzed by keyword frequency analysis, influx route analysis of data, polarity analysis via opinion mining, and positive and negative keyword analysis by polarity analysis. The results showed that nursery had the highest rank every year and education supported by Center for Children's Foodservice Management has increased significantly. The influx of data has increased through the influx route analysis of data. Blog and $caf\acute{e}e$, which have a considerable amount of information by the mother should be helpful for use as public relations and participation recruitment paths. By polarity analysis using opinion mining, the positive image of the Center for Children's Foodservice Management was increased. Therefore, the Center for Children's Foodservice Management was well-suited to the purpose and the interests of the people has been increasing steadily. In the near future, the Center for Children's Foodservice Management is expected have good recognition if various programs to participate with family are developed and advertised.

• The Journal of Fisheries Business Administration
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• v.38 no.2
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• pp.1-24
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• 2007

The improvement and richness of research in a particular domain are fundamentally based on their own various research topics and scientific or systematic research methodology. Especially considering fisheries business administration as a branch of business administration, the interdisciplinary concept will be a important factor in the research of fisheries business administration. This study analyzes fisheries business administration research through bibliometric analysis and meta-analysis to examine meta-data including research trends, researcher characteristics, and keywords. The 225 source articles are all papers published from 1990 to 2006 in the Journal of Fisheries Business Administration Society of Korea. Comparing previous research from the 80s, the major areas of Korean fisheries business administration research have changed and the rate of co-researched papers has also increased. In keyword-based meta-analysis, the topics of recent research are well balanced and diversified but some structural and editorial problems still remain. The result from meta-data and bibliometric information gathered in this study will help create guidelines for carrying out further rigorous research and enhancing the quality of research in fisheries business administration.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.543-546
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• 2017

Recently, people are using the data analysis in order to follow the new trend in information and communication technology. Media plays an important role to expand the new issue in our society, especially affected to establish social awareness about science and technology. So, We find some major technologies (Machine Learning & Blockchains) of future communication and information based on the 200 news articles through two data analysis methods such as keyword analysis and sentiment analysis. We look forward this paper to constantly develop the technology of information and communication as the guiding frame of the new scientific world.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.191-196
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• 2019

Humans use images on a daily basis-so much so that images are integral to their lives. Seeing is represented by an image, created or lived in it. Images required and developed a new paradigm from past to present. Today, images are in digital formats, and new techniques are increasing. Among them, cinemagraphs can find features that differ from previous images. The keywords found by comparing them in the image development are analyzed in detail through four characteristics in this paper. Cinemagraphs appearing in the keywords are interpreted in terms of each keyword and, through the example, the cinemagraph image can be approached concretely.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.157-169
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• 2015

In digital marketing, means of public relations and marketing of enterprises are changing into marketing techniques of predictive analytics. A significant study can be carried out by an analysis of 'the patterns of customers' uses' using big data on major portal sites and SNSs and their correlation with related keywords. This study analyzes the origins of mythological characters in major brands such as Nike, Hermes, Versace, Canon and Starbucks. Also, it extracts related keywords and relevance using big data on portal sites and SNS and their correlation. Nike marketing that reminds people of 'the goddess of victory, Nike' formed a good combination of the brand with relevance. Most of them are based on Greek mythology and have rich materials for storytelling and artistic values in common. Hopefully, this case analysis of foreign brands would become a starting point of discovering the materials of the domestic mythological characters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1442-1453
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• 2016

Now, there are prodigiously expanding worldwide economic networks in the information society, which require their social structural changes through technology innovations. This paper so tries to formally define a process-centered knowledge model to be used to analyze policy-making procedures on technology innovations. The eventual goal of the proposed knowledge model is to apply itself to analyze a topic network based upon composite keywords from a document written in a natural language format during the technology innovation procedures. Knowledge model is created to topic network that compositing driven keyword through text mining from natural language in document. And we show that the way of analyzing knowledge model and automatically generating feature keyword and relation properties into topic networks.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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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.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.164-169
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• 2022

토픽 모델링은 비즈니스 분석이나 기술 동향 파악 등 다방면에서 많이 사용되고 있는 기술이다. 하지만 대표적인 방법인 LDA와 같은 비지도학습의 경우, 그 알고리즘 구조상 문서의 수가 많을 때 토픽 모델링이 가능하다. 본 논문에서는 문서의 수가 적은 경우도, 키워드 및 키프레이즈를 이용한 군집화를 통해 토픽 모델링을 하고 감성분석을 통해 토픽에 대한 분석도 제시하였다. 이에 필요한 데이터 제작 및 키워드 추출, 키워드 기반 감성분석, 키워드 임베딩 및 군집화를 구현하였고, 결과를 정성적으로 보았을 때 유의미한 분석이 되는 것을 확인하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.133-134
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• 2021

본 연구는 최근 고등학교기관(대학)의 평가에서 가장 중심 단어가 되고 있는 있는 '핵심역량' 관련 최근 연구들의 주요 키워드들과 그들간의 네트워크를 분석하고자 한다. 본 연구에서는 2011년부터 2020년까지(최근 10년간)의 '대학 핵심역량' 관련 등재지(등재 후보지 포함)에 발표된 총 176건의 관련 연구물들을 언어 네트워크 분석 방법론을 활용하여, 주요 키워드 추출 및 워드클라우드 제시, 주요 핵심어들 간의 관계성(의미망 네트워크) 분석 등을 진행하고자 한다. 이와 같은 연구 결과는 관련 학자들이 연구를 진행할 때, 대학 관계자가 학교단위 교육활동 계획 기획 및 평가활동을 할 때 매우 중요한 기초 자료로 활용될 것으로 기대된다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.261-262
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• 2023

본 연구에서는 감성 분석 기반의 키워드 도출형 영화 리뷰 웹사이트를 개발하였다. 사용자들은 영화에 대한 리뷰를 작성할 때, 자동으로 키워드를 추출하는 기능을 활용하여 다양하면서도 빠르게 정보를 얻을 수 있다. 사용자가 작성한 리뷰를 시스템에 입력하면, 내부적으로 ChatGPT를 활용하여 텍스트를 분석하고 키워드를 추출한다. 이를 통해 사용자는 별다른 노력 없이도 키워드를 통해 영화의 장르, 감독, 배우, 플롯 요소 등 다양한 정보를 빠르게 확인할 수 있다. 추출된 키워드는 저장되어 시각화에 활용되며, 사용자들은 리뷰에 대한 원하는 정보를 쉽게 얻을 수 있다. 개발된 키워드 도출형 영화 리뷰 웹사이트는 사용자들에게 빠르고 다양한 정보를 제공하며, 영화 관련 결정을 내리는 데에 도움을 줄 것으로 기대된다.