• Title/Summary/Keyword: Unstructured data analysis

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Development of Data Visualization Tools for Land-Based Fish Farm Big Data Analysis System (육상 양식장 빅데이터 분석 시스템 개발을 위한 데이터 시각화 도구 개발)

  • Seoung-Bin Ye;Jeong-Seon Park;Hyi-Thaek Ceong;Soon-Hee Han
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.4
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    • pp.763-770
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    • 2024
  • Currently, land-based fish farms utilizing seawater have introduced and are utilizing various equipment such as real-time water quality monitoring systems, facility automation systems, and automated dissolved oxygen supply devices. Furthermore, data collected from various equipment in these fish farms produce structured and unstructured big data related to water quality environment, facility operations, and workplace visual information. The big data generated in the operational environment of fish farms aims to improve operational and production efficiency through the development and application of various methods. This study aims to develop a system for effectively analyzing and visualizing big data produced from land-based fish farms. It proposes a data visualization process suitable for use in a fish farm big data analysis system, develops big data visualization tools, and compares the results. Additionally, it presents intuitive visualization models for exploring and comparing big data with time-series characteristics.

A Study on the Perception of Quality of Care Services by Care Workers using Big Data (빅데이터를 활용한 요양보호사의 서비스질 인식에 관한 연구)

  • Han-A Cho
    • Journal of Korean Dental Hygiene Science
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    • v.6 no.1
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    • pp.13-25
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    • 2023
  • Background: This study was conducted to confirm the service quality management of care workers, who are direct service personnel of long-term care insurance for the elderly, using unstructured big data. Methods: Using a textome, this study collected and analyzed unstructured social data related to care workers' service quality. Frequency, TF-IDF, centrality, semantic network, and CONCOR analyses were conducted on the top 50 keywords collected by crawling the data. Results: As a result of frequency analysis, the top-ranked keywords were 'Long-term care services,' 'Care workers,' 'Quality of care services,' 'Long term care,' 'Long term care facilities,' 'Enhancement,' 'Elderly,' 'Treatment,' 'Improvement,' and 'Necessity.' The results of degree centrality and eigenvector centrality were almost the same as those of the frequency analysis. As a result of the CONCOR analysis, it was found that the improvement in the quality of long-term care services, the operation of the long-term care services, the long-term care services system, and the perception of the psychological aspects of the care workers were of high concern. Conclusion: This study contributes to setting various directions for improving the service quality of care workers by presenting perceptions related to the service quality of care workers as a meaningful group.

a Study on Using Social Big Data for Expanding Analytical Knowledge - Domestic Big Data supply-demand expectation - (분석지의 확장을 위한 소셜 빅데이터 활용연구 - 국내 '빅데이터' 수요공급 예측 -)

  • Kim, Jung-Sun;Kwon, Eun-Ju;Song, Tae-Min
    • Knowledge Management Research
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    • v.15 no.3
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    • pp.169-188
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    • 2014
  • Big data seems to change knowledge management system and method of enterprises to large extent. Further, the type of method for utilization of unstructured data including image, v ideo, sensor data a nd text may determine the decision on expansion of knowledge management of the enterprise or government. This paper, in this light, attempts to figure out the prediction model of demands and supply for big data market of Korea trough data mining decision making tree by utilizing text bit data generated for 3 years on web and SNS for expansion of form for knowledge management. The results indicate that the market focused on H/W and storage leading by the government is big data market of Korea. Further, the demanders of big data have been found to put important on attribute factors including interest, quickness and economics. Meanwhile, innovation and growth have been found to be the attribute factors onto which the supplier puts importance. The results of this research show that the factors affect acceptance of big data technology differ for supplier and demander. This article may provide basic method for study on expansion of analysis form of enterprise and connection with its management activities.

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Cross-national Analysis of Robot Research Using Non-Structured Text Analytics for R&D Policy

  • Kim, Jeong Hun;Seo, Han Sol;Lee, Jae Woong;Lee, Jung Won;Kwon, Oh Byung
    • Asia Pacific Journal of Business Review
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    • v.1 no.2
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    • pp.63-88
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    • 2017
  • With the advent of new frontiers in robotics, the spectrum of robot research area has widened in many fields and applications. Other than conventional robot research, many technologies such as smart devices, drones, healthcare robots, and soft robots are emerging as promising applications. Due to the research complexity of this topic, this research requires international collaboration and should be fertilized by R&D policies. This paper aims to propose a method to perform a cross-national analysis of robot research with unstructured data such as papers in the proceedings of an international conference. Text analytics are applied to extract research issues and applications in an automatic manner.

Design and Implementation of Hadoop-based Big-data processing Platform for IoT Environment (사물인터넷 환경을 위한 하둡 기반 빅데이터 처리 플랫폼 설계 및 구현)

  • Heo, Seok-Yeol;Lee, Ho-Young;Lee, Wan-Jik
    • Journal of Korea Multimedia Society
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    • v.22 no.2
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    • pp.194-202
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    • 2019
  • In the information society represented by the Fourth Industrial Revolution, various types of data and information that are difficult to see are produced, processed, and processed and circulated to enhance the value of existing goods. The IoT(Internet of Things) paradigm will change the appearance of individual life, industry, disaster, safety and public service fields. In order to implement the IoT paradigm, several elements of technology are required. It is necessary that these various elements are efficiently connected to constitute one system as a whole. It is also necessary to collect, provide, transmit, store and analyze IoT data for implementation of IoT platform. We designed and implemented a big data processing IoT platform for IoT service implementation. Proposed platform system is consist of IoT sensing/control device, IoT message protocol, unstructured data server and big data analysis components. For platform testing, fixed IoT devices were implemented as solar power generation modules and mobile IoT devices as modules for table tennis stroke data measurement. The transmission part uses the HTTP and the CoAP, which are based on the Internet. The data server is composed of Hadoop and the big data is analyzed using R. Through the emprical test using fixed and mobile IoT devices we confirmed that proposed IoT platform system normally process and operate big data.

Development of integrated management solution through log analysis based on Big Data (빅데이터기반의 로그분석을 통한 통합 관리 솔루션 개발)

  • Kang, Sun-Kyoung;Lee, Hyun-Chang;Shin, Seong-Yoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.541-542
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    • 2017
  • In this paper, we intend to develop an integrated management solution that can be easily operated by integrating complex and various cloud environments. This has the advantage that users and administrators can conveniently solve problems by collecting and analyzing fixed log data and unstructured log data based on big data and realizing integrated monitoring in real time. Hypervisor log pattern analysis technology will be able to manage existing complex and various cloud environment more efficiently.

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A Research on Difference Between Consumer Perception of Slow Fashion and Consumption Behavior of Fast Fashion: Application of Topic Modelling with Big Data

  • YANG, Oh-Suk;WOO, Young-Mok;YANG, Yae-Rim
    • The Journal of Economics, Marketing and Management
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    • v.9 no.1
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    • pp.1-14
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    • 2021
  • Purpose: The article deals with the proposition that consumers' fashion consumption behavior will still follow the consumption behavior of fast fashion, despite recognizing the importance of slow fashion. Research design, data and methodology: The research model to verify this proposition is topic modelling with big data including unstructured textual data. we combined 5,506 news articles posted on Naver news search platform during the 2003-2019 period about fast fashion and slow fashion, high-frequency words have been derived, and topics have been found using LDA model. Based on these, we examined consumers' perception and consumption behavior on slow fashion through the analysis of Topic Network. Results: (1) Looking at the status of annual article collection, consumers' interest in slow fashion mainly began in 2005 and showed a steady increase up to 2019. (2) Term Frequency analysis showed that the keywords for slow fashion are the lowest, with consumers' consumption patterns continuing around 'brand.' (3) Each topic's weight in articles showed that 'social value' - which includes slow fashion - ranked sixth among the 9 topics, low linkage with other topics. (4) Lastly, 'brand' and 'fashion trend' were key topics, and the topic 'social value' accounted for a low proportion. Conclusion: Slow fashion was not a considerable factor of consumption behavior. Consumption patterns in fashion sector are still dominated by general consumption patterns centered on brands and fast fashion.

Building Modeling for Unstructured Data Analysis Using Big Data Processing Technology (빅데이터 처리 기술을 활용한 비정형데이터 분석 모델링 구축)

  • Kim, Jung-Hoon;Kim, Sung-Jin;Kwon, Gi-Yeol;Ju, Da-Hye;Oh, Jae-Yong;Lee, Jun-Dong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2020.07a
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    • pp.253-255
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    • 2020
  • 기업 및 기관 데이터는 워드프로세서, 프레젠테이션, 이메일, open api, 엑셀, XML, JSON 등과 같은 텍스트 기반의 비정형 데이터로 구성되어 있습니다. 텍스트 마이닝(Textmining)을 통해서 자연어 처리 및 기계학습 등의 기술을 이용하여 정보의 추출부터 요약·분류·군집·연관도 분석 등의 과정을 수행울 진행한다. 다양한 시각화 데이터를 보여줄 수 있는 다양한 모델 구축을 진행한 후 민원 신청 내용을 분석 및 변환 작업을 진행한다. 본 논문은 AI 기술과 빅데이터를 활용하여 민원을 분석을 하여 알맞은 부서에 민원을 자동으로 할당해 주는 기술을 다룬다.

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A Study on Construction of Crime Prevention System using Big Data in Korea (한국에서 빅데이터를 활용한 범죄예방시스템 구축을 위한 연구)

  • Kim, SungJun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.5
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    • pp.217-221
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    • 2017
  • Proactive prevention is important for crime. Past crimes have focused on coping after death and punishing them. But with Big Data technology, crime can be prevented spontaneously. Big data can predict the behavior of criminals or potential criminals. This article discusses how to build a big data system for crime prevention. Specifically, it deals with the way to combine unstructured data of big data with basic form data, and as a result, designs crime prevention system. Through this study, it is expected that the possibility of using big data for crime prevention is described through fingerprints, and it is expected to help crime prevention program and research in future.

Analysis of Networks among Design Engineers Using Product Data Objects (제품자료 객체를 이용한 설계자 네트워크 분석)

  • Cha, Chun-Nam;Do, Namchul
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.39 no.3
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    • pp.139-146
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    • 2016
  • This study proposes a methodology to analyse social networks among participating design engineers during product development projects. The proposed methodology enables product development managers or the participating design engineers to make a proper decision on product development considering the performance of participating design engineers. It considers a product development environment where an integrated product data management (PDM) system manages the product development data and associated product development processes consistently in its database, and all the design engineers share the product development data in the PDM database for their activities in the product development project. It provides a novel approach to build social networks among design engineers from an operational product development data in the PDM database without surveys or monitoring participating engineers. It automatically generates social networks among the design engineers from the product data and relationships specified by the participants during the design activities. It allows analysts to gather operational data for their analysis without additional efforts for understanding complex and unstructured product development processes. This study also provides a set of measures to evaluate the social networks. It will show the role and efficiency of each design engineers in the social network. To show the feasibility of the approach, it suggests an architecture of social network analysis (SNA) system and implemented it with a research-purpose PDM system and R, a statistical software system. A product configuration management process with synthetical example data is applied to the SNA system and it shows that the approach enables analysts to evaluate current position of design engineers in their social networks.