• Title/Summary/Keyword: Bigdata Platform

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Designing Cost Effective Open Source System for Bigdata Analysis (빅데이터 분석을 위한 비용효과적 오픈 소스 시스템 설계)

  • Lee, Jong-Hwa;Lee, Hyun-Kyu
    • Knowledge Management Research
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    • v.19 no.1
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    • pp.119-132
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    • 2018
  • Many advanced products and services are emerging in the market thanks to data-based technologies such as Internet (IoT), Big Data, and AI. The construction of a system for data processing under the IoT network environment is not simple in configuration, and has a lot of restrictions due to a high cost for constructing a high performance server environment. Therefore, in this paper, we will design a development environment for large data analysis computing platform using open source with low cost and practicality. Therefore, this study intends to implement a big data processing system using Raspberry Pi, an ultra-small PC environment, and open source API. This big data processing system includes building a portable server system, building a web server for web mining, developing Python IDE classes for crawling, and developing R Libraries for NLP and visualization. Through this research, we will develop a web environment that can control real-time data collection and analysis of web media in a mobile environment and present it as a curriculum for non-IT specialists.

Producing method of e-learning contents by collective intelligence (집단지성을 발현한 학습 컨텐츠 제작 방법)

  • Lee, Doo-young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.759-760
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    • 2013
  • Duaring IT industrial trend time, there are many important concept. Cloud computing, Bigdata issue, etc. One of the most important concept is 'Web 2.0' On educational industry, there is not enough up-dated at Web 2.0 concept. It has still One way study model. So apply 'web 2.0' concept on educational platform, and especially e-learning class, we can apply 'collective intelligence' concept.

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Agriculture Bigdata Management and AI Research Platform Development (농업 빅데이터 관리 및 인공지능 연구 플랫폼 개발)

  • Kim, Ki-Hyeon;Seok, Woojin;Moon, Junghoon;Kim, Kwangsoo;Sim, Joonyong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.507-509
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    • 2022
  • 농업은 우리의 삶에서 빼놓을 수 없는 중요한 분야이며, 농업은 토지를 이용하여 다양한 작물들을 길러 음식을 만드는 기본이라고 말할 수 있다. 이렇게 중요한 농업 분야를 ICT 분야에서 가장 이슈가 되는 기술인 인공지능 기술과 결합하여 스마트팜과 같은 농업의 디지털화를 구축할 수 있다. 이와 같은 스마트팜 구축을 위해서는 기본적으로 다양한 작물의 빅데이터를 제공하고, 이 데이터를 바탕으로 인공지능을 수행하여 다양한 결과를 제공할 수 있다. 하지만 인공지능 연구를 수행하기 위한 시스템 및 플랫폼의 부재라는 문제점이 존재한다. 이러한 문제점을 해결하기 위해 농업 빅데이터 관리 및 인공지능 연구 플랫폼 개발을 위한 과제를 통해 농업 빅데이터를 관리하고 인공지능을 연구자들이 손쉽게 수행할 수 있는 플랫폼을 개발하여 농업 분야의 작물 생산성 향상에 기여하고자 한다.

Integration of Six Sigma and BPM for Continuous Process Improvement (지속적 프로세스 개선을 위한 6시그마와 BPM 통합 모형)

  • Yoon, Ji Hyun;Jung, Jae-Yoon
    • The Journal of Bigdata
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    • v.2 no.1
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    • pp.5-15
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    • 2017
  • Six Sigma has been adopted for the last two decades in many industries of manufacturing and service business to implement processs improvement. The methodology has difficulties in discovering target projects in the Define step and in controlling continuous measure and control in the Control step. To address the problem, more advanced system is required to support continuous control and management, and business process management (BPM) can be an effective solution for this problem. In this research, we introduce integrated models of Six Sigma and BPM for the purpose of realizing continuous process improvement, and explain the procedure of analyzing, improving, and monitoring the processes based on the data which has been accumulated in business process execution. It is expected that this integrated approach can maximize business performance by improving and managing business continuously on the integrated platform of two business innovation strategies, Six Sigma and BPM.

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A Study on Subscriber's Preference Factors through Korea, United States and Japan Webtoon Data Analysis : With Naver Webtoon (한, 미, 일 웹툰 분석을 통한 구독자 선호 요인 탐색 : 네이버 웹툰을 중심으로)

  • Do, Sang-Beum;Kang, Juyoung
    • The Journal of Bigdata
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    • v.3 no.1
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    • pp.21-32
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    • 2018
  • Currently, Webtoon Industry is promising as high potential market from it's high growth trend. The best advantage webtoon propose is that webtoon can provide appropriate service to customers with various needs. For this feature, webtoon industry is expanding throughout the world. This situation may give a great chance for authors and webtoon service corporation to export webtoon contents. Also, this situation could be an opportunity for webtoon to become a new "Korean Wave" contents. For successful advance to market, a close analysis for customers of exporting countries. In this research, we collected the data from Naver Webtoon and analyzed the features of webtoons and webtoon subscribers according to countries. With this research, it would be possible to find out specific methods and variables which affect the preference of webtoon subscribers.

A study on how to advance the student management system for innovative university education (혁신적 대학교육을 위한 학생관리시스템 고도화 방안 연구)

  • Minsu Kim;Hyun-Ku Min
    • Convergence Security Journal
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    • v.22 no.5
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    • pp.89-94
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    • 2022
  • Efforts to improve the quality of university education, that is, advanced plans for innovative university education, are needed in the face of changes in educational demand due to rapid changes in new industries and society and the competition for survival due to a rapidly decreasing school-age population with the full-fledged start of the era of the 4th industrial revolution is being demanded. In particular, it is necessary to apply a system for student counseling and guidance management through college life adjustment diagnosis from students entering college to graduation. Accordingly, each university is promoting a project to upgrade a course-linked integrated platform based on core technologies of the 4th industrial revolution era, such as big data and artificial intelligence (AI). Therefore, in this study, based on the field of information security major, we intend to present a plan to advance the student management system for innovative university education.

A Study on The Effect of Perceived Value and Innovation Resistance Factors on Adoption Intention of Artificial Intelligence Platform: Focused on Drug Discovery Fields (인공지능(AI) 플랫폼의 지각된 가치 및 혁신저항 요인이 수용의도에 미치는 영향: 신약 연구 분야를 중심으로)

  • Kim, Yeongdae;Kim, Ji-Young;Jeong, Wonkyung;Shin, Yongtae
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.12
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    • pp.329-342
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    • 2021
  • The pharmaceutical industry is experiencing a productivity crisis with a low probability of success despite a long period of time and enormous cost. As a strategy to solve the productivity crisis, the use cases of Artificial Intelligence(AI) and Bigdata are increasing worldwide and tangible results are coming out. However, domestic pharmaceutical companies are taking a wait-and-see attitude to adopt AI platform for drug research. This study proposed a research model that combines the Value-based Adoption Model and the Innovation Resistance Model to empirically study the effect of value perception and resistance factors on adopting AI Platform. As a result of empirical verification, usefulness, knowledge richness, complexity, and algorithmic opacity were found to have a significant effect on perceived values. And, usefulness, knowledge richness, algorithmic opacity, trialability, technology support infrastructure were found to have a significant effect on the innovation resistance.

Efficient Association Rule Mining based SON Algorithm for a Bigdata Platform (빅데이터 플랫폼을 위한 SON알고리즘 기반의 효과적인 연관 룰 마이닝)

  • Nguyen, Giang-Truong;Nguyen, Van-Quyet;Nguyen, Sinh-Ngoc;Kim, Kyungbaek
    • Journal of Digital Contents Society
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    • v.18 no.8
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    • pp.1593-1601
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    • 2017
  • In a big data platform, association rule mining applications could bring some benefits. For instance, in a agricultural big data platform, the association rule mining application could recommend specific products for farmers to grow, which could increase income. The key process of the association rule mining is the frequent itemsets mining, which finds sets of products accompanying together frequently. Former researches about this issue, e.g. Apriori, are not satisfying enough because huge possible sets can cause memory to be overloaded. In order to deal with it, SON algorithm has been proposed, which divides the considered set into many smaller ones and handles them sequently. But in a single machine, SON algorithm cause heavy time consuming. In this paper, we present a method to find association rules in our Hadoop based big data platform, by parallelling SON algorithm. The entire process of association rule mining including pre-processing, SON algorithm based frequent itemset mining, and association rule finding is implemented on Hadoop based big data platform. Through the experiment with real dataset, it is conformed that the proposed method outperforms a brute force method.

An elastic distributed parallel Hadoop system for bigdata platform and distributed inference engines (동적 분산병렬 하둡시스템 및 분산추론기에 응용한 서버가상화 빅데이터 플랫폼)

  • Song, Dong Ho;Shin, Ji Ae;In, Yean Jin;Lee, Wan Gon;Lee, Kang Se
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.5
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    • pp.1129-1139
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    • 2015
  • Inference process generates additional triples from knowledge represented in RDF triples of semantic web technology. Tens of million of triples as an initial big data and the additionally inferred triples become a knowledge base for applications such as QA(question&answer) system. The inference engine requires more computing resources to process the triples generated while inferencing. The additional computing resources supplied by underlying resource pool in cloud computing can shorten the execution time. This paper addresses an algorithm to allocate the number of computing nodes "elastically" at runtime on Hadoop, depending on the size of knowledge data fed. The model proposed in this paper is composed of the layered architecture: the top layer for applications, the middle layer for distributed parallel inference engine to process the triples, and lower layer for elastic Hadoop and server visualization. System algorithms and test data are analyzed and discussed in this paper. The model hast the benefit that rich legacy Hadoop applications can be run faster on this system without any modification.

Digital Transformation Based on Chatbot in Legacy Environment (챗봇을 이용한 Legacy 환경의 Digital Transformation)

  • Jang, Jeong-ho;Kim, Jin-soo;Lee, Kang-Yoon
    • The Journal of Bigdata
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    • v.3 no.2
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    • pp.79-85
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    • 2018
  • As the utilization of chatbots grows and the AI market grows, many companies are interested. And everybody is spurring growth by offering chatbot build services so that they can create chatbots. This makes chatbots easier to service on the messenger platform, which is changing the existing application market. In this paper, we present a methodology for designing and implementing existing DB-based applications as instant messenger platform-based applications, and summarize what to consider in actual implementation to provide an optimal system structure. According to this methodology, we design and implement a chatbot that serves as an teaching advisor who provides information to the students in the curriculum. The implemented application objectively visualizes the user's desired information from the user's point of view and delivers it through the interactive interface quickly and intuitively. By implementing these services and real service, it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. Enterprise legacy application will take chatbot technology as one of important digital transformation initiative.