• Title/Summary/Keyword: TextMining

Search Result 1,563, Processing Time 0.022 seconds

Analysis of the Core Concepts of Middle School Informatics Textbook Using Big Data Analysis Techniques (빅데이터 분석 방법을 이용한 중학교 정보 교과서 핵심 개념 분석)

  • Woon, Daewoong;Choe, Hyunjong
    • Journal of Creative Information Culture
    • /
    • v.5 no.2
    • /
    • pp.157-164
    • /
    • 2019
  • Big data is a field that has been utilized and developed in various fields in our society recently. Big data analysis techniques are frequently used to analyze various big data in various fields of politics, economy, and society to grasp various meanings hidden in the data. However, big data analysis is used some case studies of in fields of analysis of educational data, but analysis of the curriculum and direction is still inadequate. Therefore, this study aims to identify and analyze the core concepts of middle school informatics textbooks using big data analysis techniques. Text mining was used for big data analysis for informatics textbook analysis. Through the core concepts of middle school informatics textbooks identified using this techniques, we could confirm the concepts to be emphasized in the textbooks and the possibility of using big data in the field of education.

Development of Dog Name Recommendation System for the Image Abstraction (이미지 추상화 기법을 이용한 반려견 이름 추천 시스템 개발)

  • Jae-Heon Lee;Ye-Rin Jeong;Mi-Kyeong Moon;Seung-Min Park
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.18 no.2
    • /
    • pp.313-320
    • /
    • 2023
  • The cumulative registration status of dogs is from 1.07 million in 2016 to 2.32 million in 2020. Animal registration is increasing by more than 10% every year, and accordingly, a name must be decided when registering a dog. We want to give a name that fits the characteristics of a dog's appearance, but there are many difficulties in naming it. This paper explains the development of a system for recognizing dog images and recommends dog names based on similar objects or food. This system extracts similarities with dogs' images through models that learn images of various objects and foods, and recommends dog names based on similarities. In addition, by recommending additional related words based on the image data of the result value, it was possible to provide users with various options, increase convenience, and increase interest and fun. Through this system, it is expected that users will be able to solve their concerns about naming their dogs, check names that suit their dogs comfortably, and give them various options through various recommended names to increase satisfaction.

A Study on Implications of AI Education Policy using Keyword Analysis (키워드 분석을 활용한 인공지능 교육 정책의 시사점 연구)

  • Jaeho Lee;Hongwon Jeong
    • Journal of The Korean Association of Information Education
    • /
    • v.26 no.5
    • /
    • pp.397-406
    • /
    • 2022
  • In this study, We confirmed the three major policy directions presented in "Educational Policy Direction and Core Tasks in the Age of Artificial Intelligence" announced by the government in 2020, and analyzed how the direction and key tasks are reflected in the policy from keywords selected from government policy data related to artificial intelligence education published between '20 and '22. It was extracted and analyzed how the direction and key tasks are reflected in the policy. As a result of text mining and the topic analysis, the direction of education set was analyzed and various types of activities for nurturing talents in the field of artificial intelligence were confirmed. Ultimately, the government's policy direction is to apply the '25 revised curriculum in earnest, while advancing and activating the AI education policy and allowing it to settle naturally in the field. It could be predicted that related policies and tasks would appear more and more.

A Study on Correlation Analysis of One-Person Housing Space Design Convergence Contents by Using Social Network Analysis (소셜 네트워크 분석 방법론을 활용한 1인 주거공간디자인 융합콘텐츠 상관관계 분석)

  • Park, Eun Soo;Kim, Ji Eun
    • Korea Science and Art Forum
    • /
    • v.34
    • /
    • pp.133-148
    • /
    • 2018
  • Korea's housing structure is predicted that one-person housing will be the most common type of housing in Korea. Therefore, this study intends to derive contents for designing a one-person housing space considering the life of a rapidly increasing one-person householder. For this purpose, this study objectively derives the social, economic and cultural influencing factors of one-person households through big data analysis, and analyzed the correlation between contents using social network analysis methodology. In this paper, 60 core contents related to one person housing space were derived by applying big data analysis methodology. And through social network analysis, the most influential contents were derived from the space editing and space composition categories. This means that the residential space is an important part of the design idea that can flexibly respond to changes in the user's life. Based on this study, future research will focus on the concept and design methodology of one-person housing space.

Big Data Application for Judgment on Consumer's Awareness of the Trademark (상표의 소비자 인식 판단을 위한 빅데이터 활용 방안)

  • You, Hyun-Woo;Lee, Hwan-soo
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
    • /
    • v.6 no.8
    • /
    • pp.399-408
    • /
    • 2016
  • As entering the Big Data age, utilization of Big Data is also increasing in the intellectual property sector. Meanwhile, the purpose of a trademark which distinguishes the source of the goods essentially is to enable the public to recognize the goods. Big Data technologies which is recently becoming a issue can be used as a tool to judge consumer's awareness of the trademark. It was difficult for judgment of trademark awareness through traditional ways. As a new way, survey methodology has bee received attention, and it was applied to the field of trademark law. However, various problems such as cost, time, objectivity, and fairness were observed. In order to overcome theses limitations, this study proposes new way utilizing big data analytics for judgment on consumer's awareness of the trademark. This new way will not only contribute to enhancing the objectivity of judging trademark awareness but also utilized to support for related legal judgments.

Stock Market Prediction Using Sentiment on YouTube Channels (유튜브 주식채널의 감성을 활용한 코스피 수익률 등락 예측)

  • Su-Ji, Cho;Cheol-Won Yang;Ki-Kwang Lee
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.46 no.2
    • /
    • pp.102-108
    • /
    • 2023
  • Recently in Korea, YouTube stock channels increased rapidly due to the high social interest in the stock market during the COVID-19 period. Accordingly, the role of new media channels such as YouTube is attracting attention in the process of generating and disseminating market information. Nevertheless, prior studies on the market forecasting power of YouTube stock channels remain insignificant. In this study, the market forecasting power of the information from the YouTube stock channel was examined and compared with traditional news media. To measure information from each YouTube stock channel and news media, positive and negative opinions were extracted. As a result of the analysis, opinion in channels operated by media outlets were found to be leading indicators of KOSPI market returns among YouTube stock channels. The prediction accuracy by using logistic regression model show 74%. On the other hand, Sampro TV, a popular YouTube stock channel, and the traditional news media simply reported the market situation of the day or instead showed a tendency to lag behind the market. This study is differentiated from previous studies in that it verified the market predictive power of the information provided by the YouTube stock channel, which has recently shown a growing trend in Korea. In the future, the results of advanced analysis can be confirmed by expanding the research results for individual stocks.

Visualizing Unstructured Data using a Big Data Analytical Tool R Language (빅데이터 분석 도구 R 언어를 이용한 비정형 데이터 시각화)

  • Nam, Soo-Tai;Chen, Jinhui;Shin, Seong-Yoon;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2021.05a
    • /
    • pp.151-154
    • /
    • 2021
  • Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study was analyzed for 21 papers in the March 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 305 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

  • PDF

Visualizing Article Material using a Big Data Analytical Tool R Language (빅데이터 분석 도구 R 언어를 이용한 논문 데이터 시각화)

  • Nam, Soo-Tai;Shin, Seong-Yoon;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2021.05a
    • /
    • pp.326-327
    • /
    • 2021
  • Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

  • PDF

Development of Social Data Collection and Loading Engine-based Reliability analysis System Against Infectious Disease Pandemic (감염병 위기 대응을 위한 소셜 데이터 수집 및 적재 엔진 기반 신뢰도 분석 시스템 개발)

  • Doo Young Jung;Sang-Jun Lee;MIN KYUNG IL;Seogsong Jeong;HyunWook Han
    • The Journal of Bigdata
    • /
    • v.7 no.2
    • /
    • pp.103-111
    • /
    • 2022
  • There are many institutions, organizations, and sites related to responding to infectious diseases, but as the pandemic situation such as COVID-19 continues for years, there are many changes in the initial and current aspects, and accordingly, policies and response systems are evolving. As a result, regional gaps arise, and various problems are scattered due to trust, distrust, and implementation of policies. Therefore, in the process of analyzing social data including information transmission, Twitter data, one of the major social media platforms containing inaccurate information from unknown sources, was developed to prevent facts in advance. Based on social data, which is unstructured data, an algorithm that can automatically detect infectious disease threats is developed to create an objective basis for responding to the infectious disease crisis to solidify international competitiveness in related fields.

A Study of Information Literacy Curriculum Using Topic Modeling (토픽모델링을 활용한 정보활용교육 연구주제 분석 및 교육내용 제안)

  • Jihye, Yun;Yoo Kyung, Jeong
    • Journal of the Korean Society for information Management
    • /
    • v.39 no.4
    • /
    • pp.1-21
    • /
    • 2022
  • The aim of this study is to identify the research topics and suggest an information literacy curriculum by analyzing research articles on information literacy. For this purpose, we applied the topic modeling technique to 97 scientific articles and identified the core contents of information literacy education, such as media literacy, information literacy instruction, and the use of information resources. Based on the analysis results, we suggested an information literacy curriculum by considering the Big 6 model, information literacy standards of American Association of School Library, and Association of College and Research Libraries's information literacy competencies. This study is significant in that it considered 'use of information resources' and 'information ethics' to suggest information literacy education.