• Title/Summary/Keyword: 빅데이터플랫폼

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A Study on the Application of the Technology Tree for Water Hazard Information Platform (수재해 정보 플랫폼을 위한 기술트리 활용 방안 연구)

  • Kim, Dong-Young;Lee, Jeong-Ju;Chae, Hyo-Sok;Hwang, Eui-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.4
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    • pp.200-214
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    • 2014
  • Technology planning is becoming increasingly important with the rapid development and decline of technology. Technology roadmapping is a tool used to select whether the specific technique of technology planning should pursue which technology and in which time. This technology is important to secure the uncertain future since it will provide a method that is able to share the goals and strategies between organizations. Therefore, technology tree in the planning stage of the problem would be a very useful tool. In this study, both domestic and international technology tree application cases were analyzed to be able to derive a plan for ensuring that the research performed and the requirements are met for the future development and implementation of a convergence portal system. The six major systems that aim at water hazard information platform are basic information providing system, analysis information providing system, water disaster theme providing system, national disaster information system, water disaster augmented reality system and open information platform system. General standardized core technologies corresponding to the needed functions in each target system are derived through brainstorming, and classified according to the technology field to derive the technology tree.

Experiencing with Splunk, a Platform for Analyzing Machine Data, for Improving Recruitment Support Services in WorldJob+ (머신 데이터 분석용 플랫폼 스플렁크를 이용한 취업지원 서비스 개선에 관한 연구 : 월드잡플러스 사례를 중심으로)

  • Lee, Jae Deug;Rhee, MoonKi Kyle;Kim, Mi Ryang
    • Journal of Digital Convergence
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    • v.16 no.3
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    • pp.201-210
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    • 2018
  • WorldJob+, being operated by The Human Resources Development Service of Korea, provides a recruitment support services to overseas companies wanting to hire talented Korean applicants and interns, and support the entire course from overseas advancement information check to enrollment, interview, and learning for young job-seekers. More than 300,000 young people have registered in WorldJob+, an overseas united information network, for job placement. To innovate WorldJob+'s services for young job-seekers, Splunk, a powerful platform for analyzing machine data, was introduced to collate and view system log files collected from its website. Leveraging Splunk's built-in data visualization and analytical features, WorldJob+ has built custom tools to gain insight into the operation of the recruitment supporting service system and to increase its integrity. Use cases include descriptive and predictive analytics for matching up services to allow employers and job seekers to be matched based on their respective needs and profiles, and connect jobseekers with the best recruiters and employers on the market, helping job seekers secure the best jobs fast. This paper will cover the numerous ways WorldJob+ has leveraged Splunk to improve its recruitment supporting services.

Adaptive Frequent Pattern Algorithm using CAWFP-Tree based on RHadoop Platform (RHadoop 플랫폼기반 CAWFP-Tree를 이용한 적응 빈발 패턴 알고리즘)

  • Park, In-Kyu
    • Journal of Digital Convergence
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    • v.15 no.6
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    • pp.229-236
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    • 2017
  • An efficient frequent pattern algorithm is essential for mining association rules as well as many other mining tasks for convergence with its application spread over a very broad spectrum. Models for mining pattern have been proposed using a FP-tree for storing compressed information about frequent patterns. In this paper, we propose a centroid frequent pattern growth algorithm which we called "CAWFP-Growth" that enhances he FP-Growth algorithm by making the center of weights and frequencies for the itemsets. Because the conventional constraint of maximum weighted support is not necessary to maintain the downward closure property, it is more likely to reduce the search time and the information loss of the frequent patterns. The experimental results show that the proposed algorithm achieves better performance than other algorithms without scarifying the accuracy and increasing the processing time via the centroid of the items. The MapReduce framework model is provided to handle large amounts of data via a pseudo-distributed computing environment. In addition, the modeling of the proposed algorithm is required in the fully distributed mode.

Analysis of Security Technology for Internet of things (사물인터넷 보안 기술 분석)

  • Lee, Ho-Tae
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.4
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    • pp.43-48
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    • 2017
  • Today our society is approaching new intelligence information society, which has been caused by the Fourth Industrial Revolution along with the development of information and communication technology(ICT). And this has just opened a new era of Internet of Things(IoT) that connects between human and objects and between objects through network, allowing transmission and reception of information beyond the limits of space. However, many crises occurred in the existing communication environment may threaten the security of Internet of Things, by violating the three components of information security. In this paper, this study aims to analyze security technology to achieve advanced security by dividing IoT security technology for coping with security vulnerability found in different components into three groups.

Design and Implementation of a Real-Time Product Defect Detection System based on Artificial Intelligence in the Press Process (프레스 공정에서 인공지능기반 실시간 제품 불량탐지 시스템 설계 및 구현)

  • Kim, Dong-Hyun;Lee, Jae-Min;Kim, Jong-Deok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.9
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    • pp.1144-1151
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    • 2021
  • The pressing process is a compression process in which a product is made by applying force to a heated or unheated material to transform it into the desired shape. Due to the characteristics of press equipment that produces products through continuous compression for a short time, product defects occur continuously, and systems for solving these problems are being developed using various technologies. This paper proposes a real-time defect detection system based on an artificial intelligence algorithm that detects defects. By attaching various sensors to the press device, the relationship between equipment status and defects is defined and collected based on a big data platform. By developing an artificial intelligence algorithm based on the collected data and implementing the developed algorithm using an embedded board, we will show the practicality of the system by applying it to the actual field.

Exploring the Performance of Synthetic Minority Over-sampling Technique (SMOTE) to Predict Good Borrowers in P2P Lending (P2P 대부 우수 대출자 예측을 위한 합성 소수집단 오버샘플링 기법 성과에 관한 탐색적 연구)

  • Costello, Francis Joseph;Lee, Kun Chang
    • Journal of Digital Convergence
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    • v.17 no.9
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    • pp.71-78
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    • 2019
  • This study aims to identify good borrowers within the context of P2P lending. P2P lending is a growing platform that allows individuals to lend and borrow money from each other. Inherent in any loans is credit risk of borrowers and needs to be considered before any lending. Specifically in the context of P2P lending, traditional models fall short and thus this study aimed to rectify this as well as explore the problem of class imbalances seen within credit risk data sets. This study implemented an over-sampling technique known as Synthetic Minority Over-sampling Technique (SMOTE). To test our approach, we implemented five benchmarking classifiers such as support vector machines, logistic regression, k-nearest neighbor, random forest, and deep neural network. The data sample used was retrieved from the publicly available LendingClub dataset. The proposed SMOTE revealed significantly improved results in comparison with the benchmarking classifiers. These results should help actors engaged within P2P lending to make better informed decisions when selecting potential borrowers eliminating the higher risks present in P2P lending.

Success Factor and Failure Factor of Social Media in Korean Society: Based on the Word Analysis and the Network Analysis on Interview Data (한국사회에서 소셜 미디어의 성공과 실패 요인 분석: 인터뷰 데이터에 대한 어절분석·네트워크 분석을 중심으로)

  • Hong, Juhyun;Kim, Kyung-Hee
    • The Journal of the Korea Contents Association
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    • v.19 no.1
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    • pp.74-85
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    • 2019
  • This Study explores the reason why the social media like Cyworld, Iloveschool in Korea in the viewpoint if the layered model by interview. As a result the success factor in the viewpoint of layered model, user used social media for fulfilling the need for linking with other users and the social media offers the customized contents to user. Finally the social media dominated the market in advance. Facebook and Kakao talk are good examples of successful media. The failure factors are to care less about what other users want, to limit the expand of platform and not to copy with the change of the media environment. Iloveschool, Cyworld and Twitter are the examples of failure social media in Korean society. This study highlights the importance of the sensitivity of the change of environment. The expert mentioned the importance of 4th industrial revolution technology like AI, Big data and expected that new technology will emerge and the service will be developed by the change of user's taste.

AI Advisor for Response of Disaster Safety in Risk Society (위험사회 재난 안전 분야 대응을 위한 AI 조력자)

  • Lee, Yong-Hak;Kang, Yunhee;Lee, Min-Ho;Park, Seong-Ho;Kang, Myung-Ju
    • Journal of Platform Technology
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    • v.8 no.3
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    • pp.22-29
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    • 2020
  • The 4th industrial revolution is progressing by country as a mega trend that leads various technological convergence directions in the social and economic fields from the initial simple manufacturing innovation. The epidemic of infectious diseases such as COVID-19 is shifting digital-centered non-face-to-face business from economic operation, and the use of AI and big data technology for personalized services is essential to spread online. In this paper, we analyze cases focusing on the application of artificial intelligence technology, which is a key technology for the effective implementation of the digital new deal promoted by the government, as well as the major technological characteristics of the 4th industrial revolution and describe the use cases in the field of disaster response. As a disaster response use case, AI assistants suggest appropriate countermeasures according to the status of the reporter in an emergency call. To this end, AI assistants provide speech recognition data-based analysis and disaster classification of converted text for adaptive response.

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Study on Chinese Consumers' Perceptions of Samsung Smartphones through Social Media Data Analysis (소셜 미디어 데이터 분석을 통한 중국 소비자의 삼성 스마트폰에 대한 인식 연구)

  • Cui Ran;Inyong Nam
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.4
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    • pp.311-321
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    • 2024
  • This study comprehensively analyzed the perceptions of Chinese consumers who have and have not purchased Samsung smartphones, based on data from the social media platform Weibo. Various big data analysis techniques were used, including text mining, frequency analysis, centrality analysis, semantic network analysis, and CONCOR analysis. The results indicate that positive perceptions of Samsung smartphones include aspects such as design aesthetics, camera functionality, AI features, screen quality, specifications, and performance, and their status as a premium brand. On the other hand, negative perceptions include issues with pricing, a yellow tint in photos, slow charging speeds, and safety concerns. These findings will provide a crucial basis for making significant improvements in Samsung's market strategy in China.

A Study on Strengthening Personal Information Protection in Smart City (스마트시티 속 개인정보보호 강화 방안 연구)

  • Cheong, Hwan-suk;Lee, Sang-joon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.4
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    • pp.705-717
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    • 2020
  • Cities in the world are rushing to develop smart cities to create a sustainable and happy city by solving many problems in cities using information and communication technologies such as big data and IoT. However, in Korea's smart cities and smart city certification systems, the focus is on platform-oriented hardware infrastructure, and the information security aspect is first considered to build and authenticate. It is a situation in which a response system for the risk of leakage of big data containing personal information is needed through policy research on the aspect of personal information protection for smart city operation. This paper analyzes the types of personal information in smart cities, problems associated with the construction and operation of smart cities, and the limitations of the current smart city law and personal information protection management system. As a solution, I would like to present a model of a personal information protection management system in the smart city field and propose a plan to strengthen personal information protection through this. Since the management system model of this paper is applied and operated in the national smart city pilot cities, demonstration cities, and CCTV integrated control centers, it is expected that citizens' personal information can be safely managed.