• Spatial Information Research
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• v.22 no.2
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• pp.11-18
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• 2014

The aim of this study is to propose service-oriented connection model among National Geospatial Information Platforms(NGIPs). For this, the study analyzes the necessity of NGIPs connection and extracts the issues related to the connection among NGIPs through Industrial-University-Institute experts survey. Based on this analysis, this study constructs service-oriented connection model for NGIPs, so called Single Point Access model and proposes the policy and technological counterplan to realize this model. This study result can be applied to establish a platform government based on geospatial information, policy for NGIP, and the national Information plan.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1267-1280
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• 2017

This study examines the changes of the online music market and revenue models by the theory of network society and communications of Manuel Castells for the content platform. As a result of this study, we found that active communications among the members in the network, played a crucial role in the creation of contents and the promotions of profit for platform providers. It is especially important to create an environment in which members can voluntarily communicate rather than an artificial control. The content platform business consists of people, thus it has been proven that providing play elements of culture and society are important, as well as necessary conditions to the generation related to content based platform businesses.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.139-148
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• 2013

With the launch of Apple iPhone, platform and contents and design characteristics were highlights of the new factors. In addition, Smartphone users have increased explosively. In this research, we aim to analyze factors affecting on repurchase intention of a Smartphone based on Technology Acceptance Model(TAM). External factors such as platform, contents and design are identified through literature review and the influences of these factors on repurchase intention are assessed. A questionnaire survey was conducted to those who lived in Busan and Gyeongnam province. This research used Smart PLS(partial least squares) to analyze the structural relationship between those factors and repurchase intention. Analytical results show that all paths except path from platform to perceived ease of use are significant. This study suggests practical and theoretical implications based on the results.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.480-480
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• 2021

본 연구에서는 도시재생지역의 재난재해 위험성 및 회복성 분석과 현황 분석을 위한 기초 데이터의 관리와 활용성 증대를 목적으로 데이터를 등록하고 다운로드 할 수 있는 공유 플랫폼을 개발하고자 하였다. 도시재생 데이터 플랫폼은 재난재해, 지역현황, 문서 항목으로 구분하여 도시재생 정보를 서비스한다. 재난재해 항목은 폭우, 폭설, 폭염, 강풍, 지진 5개 자연재해 유형과 이로 인해 추가 피해가 발생할 수 있는 화재, 붕괴, 폭발 사회재난 3개 유형으로 구성되어있으며, 총8 종류의 재난재해 유형에 대한 위험성과 회복성 분석 DB를 제공한다. 지역현황 정보에서는 유휴공간 및 지역자산정보 등 도시재생 현황분석에 필요한 행정(통계)데이터, 시설물정보 등을 제공한다. 아울러 본 연구를 통해 산출되는 논문 및 보고서 등을 문서 항목에서 서비스한다. 데이터셋 등록 시, 시스템에 설정된 재난재해 유형, 시설물 등을 선택해 카테고리를 분류하고, 이력관리를 목적으로 데이터명과 생산년월 등에 대한 필수항목을 입력해야만 등록이 가능하도록 설정하였다. 또한 GIS 기반 공간자료 등록 시에는 가시화 서비스를 위하여 공간자료의 포맷과 좌표체계, 생산년월, 생산기관 등을 필수 입력하도록 하였으며, GIS tool을 활용한 자료 분석에 어려움이 없도록 하였다. 쇠퇴지역의 재난재해 대비/대응을 위한 도시재생 데이터 플랫폼은 금년 시범운영 후, 차년에는 클라우드 서비스 기능을 탑재해 계정 권한과 장소에 제약을 받지 않고 도시재생 업무를 수행하는 모든 사용자가 재난재해 정보를 비롯한 도시재생 관련 정보를 수집·활용할 수 있는 데이터 공유의 장을 구현함으로써 도시재생지역의 효과적인 재난재해 대비/대응 체계를 마련하고자 하였다.

• The Journal of Bigdata
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• v.7 no.2
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• pp.139-152
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• 2022

Engineering's work area for plants is a technical area that directly affects productivity, performance, and quality throughout the lifecycle from planning, design, construction, operation and disposal. Using the different types of data that occur to make decisions is important not only in the subsequent process but also in terms of cyclical cost reduction. However, there is a lack of systems to manage and analyze these integrated data. In this paper, we developed a knowledge base-based plant engineering analysis platform that can manage and utilize data. The platform provides a knowledge base that preprocesses previously collected engineering data, and provides analysis and visualization to use it as reference data in AI models. Users can perform data analysis through the use of prior technology and accumulated knowledge through the platform and use visualization in decision-support and systematically manage construction that relied only on experience.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.23-29
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• 2021

Recently, a situation in which a specific content service is impossible worldwide has occurred due to a failure of the platform service and a significant social and economic problem has been caused in the global service market. In order to secure the stability of platform services, intelligent platform operation management is required. In this study, big data flow management(BDFM) and implementation method were proposed to quickly detect to abnormal service status in the platform operation environment. As a result of analyzing, BDFM technique improved the characteristics of abnormal failure detection by more than 30% compared to the traditional NMS. The big data flow management method has the advantage of being able to quickly detect platform system failures and abnormal service conditions, and it is expected that when connected with AI-based technology, platform management is performed intelligently and the ability to prevent and preserve failures can be greatly improved.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.4
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• pp.745-754
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• 2019

As GeoWeb 2.0 technologies are widely used, various kinds of services that mashup spatial data and user data are being developed. In particular, various spatial information platforms such as Google Maps, OpenStreetMap, Daum Map, Naver Map, olleh Map, and VWorld based on GeoWeb 2.0 technologies support mashup service. The mashup service which is supported through the Open APIs of the platforms, provides various kinds of spatial data such as 2D map, 3D map, and aerial image. Also, application fields using the mashup service are greatly expanded. Recently, as user data for mashup have been greatly increased, there was a problem in mashup performance. However, the research on the mashup performance improvement is currently insufficient, even the research on the mashup performance comparison of various platforms has not been performed. In this paper, we perform comparative analysis of the mashup performance for large amounts of user data and spatial data using various spatial information platforms available in Korea. Specifically, we propose two performance analysis indexes of mashup time and user interaction time in order to analyze the mashup performance efficiently. Also, we implement a system for the performance analysis. Finally, from the performance analysis result, we propose a spatial information platform that can be efficiently applied to cases when user data increases greatly and user interaction occurs frequently.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.237-250
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• 2022

On September 28, 2020, the Korea Fair Trade Commission introduced a proposed bill entitled the "Fair Online Platform Intermediary Transactions Act." We quantify the impact of this proposed act on Naver, Korea's major digital platform. Finding a proper control unit is not an easy task in social science studies. We overcome this caveat by constructing a synthetic version of Naver using Abadie & Gardeazabal's (2003) synthetic control method. It appears that the economic cost of the proposed act is not negligible at all. Naver's opportunity loss amounted to 16.18% of its market capitalization (approximately 8.5 trillion won in comparison with its pre-regulation market capitalization). Any regulation-based approaches to resolving digital platform issues have both promises and pitfalls. The results highlight that regulatory bodies should carefully gauge the impact of such regulations, as we have seen with Naver's case.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.309-316
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• 2016

While consumption patterns have changed online music, online music platform began to emerge. While people prefer popular music recommendation, they use the online music platform chart or use the SNS Platform to share information. Online platform Ranking is different because of different properties held by members. Meanwhile, we need music charts characteristics of SNS users. So there were a lot of attempts to chart a comprehensive variety of platforms. And continue to emerge theses linking the musical characteristics and SNS. In this paper, We have developed a new chart using the behavior of Twitter Users who listen to music, and studies comparing the results with existing chart.