• 제목/요약/키워드: bigdata analysis

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The study of the field customized SW training course design based on the analysis of the field suitability of the university SW education (대학 SW 교육의 현장 적합도 분석에 기반한 현장 맞춤형 SW 교육 과정 설계에 대한 연구)

  • Cha, Joon Seub
    • Smart Media Journal
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    • v.4 no.4
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    • pp.86-92
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    • 2015
  • Recently, it is entering the hyper connectivity age due to the development of sensor and communication technology. In particular, it is emerging new industries such as the IoT, bigdata, cloud by convergence with the ICT and other industries. Because these industries are high the gravity of the software, the demand for software manpower is increasing rapidly. But university curriculum don't deviate from the traditional curriculum, and lack of positive response to these changes is occurring a mismatch with the industry demand. In this paper, investigate a software curriculums of the four-year university, and will attempt to investigate the perception about the university software course of the corporate perspective. Also, we draw a on-site fitness of universities training course by analysis of importance on software training courses between universities and businesses. Finally, we propose a strategy model for software training course design appropriate for the field.

A Study on the Research Trends on Open Innovation using Topic Modeling (토픽 모델링을 이용한 개방형 혁신 연구동향 분석 및 정책 방향 모색)

  • Cho, Sung-Bae;Shin, Shin-Ae;Kang, Dong-Seok
    • Informatization Policy
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    • v.25 no.3
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    • pp.52-74
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    • 2018
  • In February 2018, the Korean government established the "Comprehensive Plans for Government Innovation" in order to realize 'the people-centered government'. The core of the comprehensive plans is participation of the people, which is very similar to open innovation where social issues are solved by ideas and capabilities of the private sector rather than those of the government. Therefore, this study was conducted by extracting open innovation topics through topic modeling based on LDA(Latent Dirichlet Allocation) as English abstract-data from 2003, when the plans for open innovation was first announced, to April 2018. Based on the extracted results, it also conducted a comparative analysis with "Comprehensive Plans for Government Innovation." The study has significant implications in that it derives the relationship between the subjects, analyzes the present policies of Korea on open innovation and suggests directions for development.

For Improving Security Log Big Data Analysis Efficiency, A Firewall Log Data Standard Format Proposed (보안로그 빅데이터 분석 효율성 향상을 위한 방화벽 로그 데이터 표준 포맷 제안)

  • Bae, Chun-sock;Goh, Sung-cheol
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.1
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    • pp.157-167
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    • 2020
  • The big data and artificial intelligence technology, which has provided the foundation for the recent 4th industrial revolution, has become a major driving force in business innovation across industries. In the field of information security, we are trying to develop and improve an intelligent security system by applying these techniques to large-scale log data, which has been difficult to find effective utilization methods before. The quality of security log big data, which is the basis of information security AI learning, is an important input factor that determines the performance of intelligent security system. However, the difference and complexity of log data by various product has a problem that requires excessive time and effort in preprocessing big data with poor data quality. In this study, we research and analyze the cases related to log data collection of various firewall. By proposing firewall log data collection format standard, we hope to contribute to the development of intelligent security systems based on security log big data.

A domain-specific sentiment lexicon construction method for stock index directionality (주가지수 방향성 예측을 위한 도메인 맞춤형 감성사전 구축방안)

  • Kim, Jae-Bong;Kim, Hyoung-Joong
    • Journal of Digital Contents Society
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    • v.18 no.3
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    • pp.585-592
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    • 2017
  • As development of personal devices have made everyday use of internet much easier than before, it is getting generalized to find information and share it through the social media. In particular, communities specialized in each field have become so powerful that they can significantly influence our society. Finally, businesses and governments pay attentions to reflecting their opinions in their strategies. The stock market fluctuates with various factors of society. In order to consider social trends, many studies have tried making use of bigdata analysis on stock market researches as well as traditional approaches using buzz amount. In the example at the top, the studies using text data such as newspaper articles are being published. In this paper, we analyzed the post of 'Paxnet', a securities specialists' site, to supplement the limitation of the news. Based on this, we help researchers analyze the sentiment of investors by generating a domain-specific sentiment lexicon for the stock market.

Linguistic Features Discrimination for Social Issue Risk Classification (사회적 이슈 리스크 유형 분류를 위한 어휘 자질 선별)

  • Oh, Hyo-Jung;Yun, Bo-Hyun;Kim, Chan-Young
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.11
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    • pp.541-548
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    • 2016
  • The use of social media is already essential as a source of information for listening user's various opinions and monitoring. We define social 'risks' that issues effect negative influences for public opinion in social media. This paper aims to discriminate various linguistic features and reveal their effects for building an automatic classification model of social risks. Expecially we adopt a word embedding technique for representation of linguistic clues in risk sentences. As a preliminary experiment to analyze characteristics of individual features, we revise errors in automatic linguistic analysis. At the result, the most important feature is NE (Named Entity) information and the best condition is when combine basic linguistic features. word embedding, and word clusters within core predicates. Experimental results under the real situation in social bigdata - including linguistic analysis errors - show 92.08% and 85.84% in precision respectively for frequent risk categories set and full test set.

Healthcare service analysis using big data

  • Park, Arum;Song, Jaemin;Lee, Sae Bom
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.4
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    • pp.149-156
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    • 2020
  • In the Fourth Industrial Revolution, successful cases using big data in various industries are reported. This paper examines cases that successfully use big data in the medical industry to develop the service and draws implications in value that big data create. The related work introduces big data technology in the medical field and cases of eight innovative service in the big data service are explained. In the introduction, the overall structure of the study is mentioned by describing the background and direction of this study. In the literature study, we explain the definition and concept of big data, and the use of big data in the medical industry. Next, this study describes the several cases, such as technologies using national health information and personal genetic information for the study of diseases, personal health services using personal biometric information, use of medical data for efficiency of business processes, and medical big data for the development of new medicines. In the conclusion, we intend to provide direction for the academic and business implications of this study, as well as how the results of the study can help the domestic medical industry.

Evaluating real-time search query variation for intelligent information retrieval service (지능 정보검색 서비스를 위한 실시간검색어 변화량 평가)

  • Chong, Min-Young
    • Journal of Digital Convergence
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    • v.16 no.12
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    • pp.335-342
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    • 2018
  • The search service, which is a core service of the portal site, presents search queries that are rapidly increasing among the inputted search queries based on the highest instantaneous search frequency, so it is difficult to immediately notify a search query having a high degree of interest for a certain period. Therefore, it is necessary to overcome the above problems and to provide more intelligent information retrieval service by bringing improved analysis results on the change of the search queries. In this paper, we present the criteria for measuring the interest, continuity, and attention of real-time search queries. In addition, according to the criteria, we measure and summarize changes in real-time search queries in hours, days, weeks, and months over a period of time to assess the issues that are of high interest, long-lasting issues of interest, and issues that need attention in the future.

Exploratory study on the based on big data for fire prevention of multiple shops (다중이용업소의 화재예방을 위한 빅데이터 기반의 탐색적 연구)

  • Jeon, Byungkwan;Lee, Sung-Won
    • Journal of Industrial Convergence
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    • v.16 no.4
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    • pp.27-32
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    • 2018
  • In this research, in order to prevent the fire of multiple users who are concerned about many human life damage, based on the statistical data of the National Fire Protection Agency's National Fire Information Center and the Fire Defense Administration Fire Defense Administration, Attempts were made on the exploratory approach to measures that can reduce the topic of. In this research, using the preventive firefighting administrative statistics of the Fire and Disaster Management Agency, we analyzed by focusing on the effectiveness of multiple users' firefighting safety education. Through analysis results we could infer that fire safety education does not have effectiveness in actual fire prevention. Through previous research, we found out that the cause is insufficient for the management of fire safety education, thereby deriving an improvement plan to develop a systematic fire safety education system.

A Study on the Metaverse: Focused on the Application of News Big Data Service and Case Study (메타버스에 관한 연구: 뉴스 빅데이터 서비스 활용과 사례 연구를 중심으로)

  • Kim, Chang-Sik;Lee, Yunhee;Ahn, Hyunchul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.17 no.2
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    • pp.85-101
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    • 2021
  • This study aims to gain insight through understanding the Metaverse, which has recently become a hot topic. The study utilizes the methods of case study and News Bigdata Analysis Services. The Metaverse can be defined as a world with no separation between the virtual and real worlds. Currently, the Metaverse is dominated mainly by the MZ generation, but just like smartphones have quickly entered our lives, the Metaverse will soon, too, become a part of our lives. To follow up on this change, all companies, including global companies, are going after the Metaverse. Today, the Metaverse is successfully being used in all types of fields, including gaming, performing arts, business, etc., and its essential technologies include VR/AR/MR/XR and AI. This study intends to help understand the Metaverse through a case analysis of Zepeto, which has 200 million users worldwide. On Zepeto, users can decorate their own avatars, hang out with friends, go to art galleries and performances, and create and sell items. Of these users, 90% are from outside of South Korea, and 80% are teenagers. With most of the users being underage, many legal and social problems also follow. Nevertheless, who will be the first to conquer the new world of the Metaverse will continue to be a big issue. This study also analyzes domestic news articles about the Metaverse by utilizing the BigKinds system. Starting in 1996, the number of articles about the Metaverse each year remains single digit, until in 2020 when the number sharply rises to 86 news. As of June 2021, there are 1,663 articles on the Metaverse. This study suggests that the Metaverse should now be carefully examined and closely followed.

Big Data Analysis on Daegu-Gyeongbuk Administrative Integration (대구·경북 행정통합에 대한 빅데이터 분석)

  • Song, Hwa Young;Park, Han Woo
    • The Journal of the Korea Contents Association
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    • v.21 no.5
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    • pp.139-148
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    • 2021
  • The study examines public attitude and reaction regarding administrative integration in Daegu and Gyeongbuk area. Specifically, it employs social big data including textual comments on online news articles and YouTube video clips. The collected data are analyzed in order to compare two periods, that is, before and after the inauguration of the Public Opinion Committee for One Daegu-Gyeongbuk. As a result, we have found that people's favorable response to administrative integration has gradually increased since the launch of the Committee. However, it still lacks specific administrative procedures and discussion topics among the frequently used words in the collected data. Thus, the Committee needs to provide a variety of information and materials related to administrative integration.