• The Journal of Bigdata
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• v.8 no.2
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• pp.1-13
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• 2023

Current analysis of air passengers mainly relies on statistical methods, but there are limitations in analyzing detailed aspects such as travel routes, number of regional passengers and airport access times. However, with the advancement of big data technology and revised three data acts, big data-based transportation analysis has become more active. Mobile communication data, which can precisely track the location of mobile phone terminals, can serve as valuable analytical data for transportation analysis. In this paper, we propose a air passenger Origin/Destination (O/D) extraction algorithm based on mobile communication data that overcomes the limitations of existing air transportation user analysis methods. The algorithm involves setting airport signal detection zones at each airport and extracting air passenger based on their base station connection history within these zones. By analyzing the base station connection data along the passenger's origin-destination paths, we estimate the entire travel route. For this paper, we extracted O/D information for both domestic and international air passengers at all domestic airports from January 2019 to December 2020. To compensate for errors caused by mobile communication service provider market shares, we applied a adjustment to correct the travel volume at a nationwide citizen level. Furthermore correlation analysis was performed on O/D data and aviation statistics data for air traffic users based on mobile communication data to verify the extracted data. Through this, there is a difference in the total amount (4.1 for domestic and 4.6 for international), but the correlation is high at 0.99, which is judged to be useful. The proposed algorithm in this paper enables a comprehensive and detailed analysis of air transportation users' travel behavior, regional/age group ratios, and can be utilized in various fields such as formulating airport-related policies and conducting regional market analysis.

• Proceedings of the Korean Society for Information Management Conference
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• 2014.08a
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• pp.131-134
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• 2014

전 세계적으로 다양한 영역에서 빅데이터 활용 성공 사례가 증가하게 되면서 도서관 분야에서도 빅데이터를 활용한 신규 서비스 개발 필요성이 제기 되고 있다. 본 연구는 공공도서관의 정보서비스 제공 및 도서관 운영 실태, 이용자 특성 등을 분석하였고, 이를 바탕으로 새로운 도서관 패러다임을 이끄는 도서관 빅데이터 서비스 모형을 개발하고자 한다. 먼저, 설문 대상을 사서 집단과 이용자 집단으로 나누어 공공도서관 이용현황을 파악하였고, 대표적인 공공도서관 서비스인 장서개발 및 열람봉사, 이용자 맞춤형 추천서비스에 대한 수요도를 분석하였다. 추가적으로 응답에 대한 집단 간 차이에 대해 살펴보았다. 분석결과를 토대로 관련 서비스 개발을 위한 방향성을 도출하였고, 향후 활용 가능한 도서관 빅데이터 서비스 정립을 위한 기초 방안을 제시하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.308-310
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• 2018

국민의 해양활동 증가로 전체 선박사고의 약 86%가 연안에서 발생하고, 레저선박 등 중소형선박이 89%를 차지하고 있다. 선박 이용자는 복잡다양하게 증가하고 있으나, 해양안전의식이 부족하고 이에 맞는 안전관리대책이 필요하다. 레저선박 이용자의 안전항행 지원과 연안 및 마리나에서의 해양사고를 줄이기 위해 이용자가 이용하고 있는 각종 자료(기상정보, 항로정보, 마리나 정보, 주제도 등)와 해역이용자, 관제자의 의견을 반영한 해양기상, 항로정보, 안전정보, 레저 정보 등 종합적인 빅데이터를 가공하여 레저선박 이용자에게 꼭 필요한 전용항해안전 시스템 개발을 위한 기초 연구를 수행하고 있다.

• Journal of Korean Library and Information Science Society
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• v.49 no.2
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• pp.357-388
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• 2018

This study aims to analyze library user and circulation status based on the bigdata logs to identify characteristics by user group and propose methods for efficient management of library. The logs to be analyzed consist of user information, circulation information, service usage information registered at the National Library of Korea, Sejong. The user information logs contain 107,369 age data, 106,918 gender data, 106,838 residential data. The circulation information logs contain 536,083 circulation user data, 6,509,369 circulation count data, and the service usage information logs contain 82,813 data. For the analysis of characteristics by user group, the data were used for analyzing user status by age, gender, residence and circulation status by year, month, day. In addition, this study conducts FGI(Focus Group Interview) and linkage analysis with external data to identify factors for analysis results. Based on analysis results, improvement methods for helping library make effective decision-making were proposed. This study analyze empirically user and circulation status based on bigdata logs, and it has significance for being different form proceeding researches with less analysis data.

• Journal of the Korean Society for information Management
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• v.32 no.2
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• pp.63-86
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• 2015

Big data refers to dataset whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze. And now it is considered to create the new opportunity in every industry. The purpose of this study is to develop of big data services in public library for improved library services. To this end, analysed the type of library big data and needs of stockholders through the various methods such as deep interview, focus group interview, questionnaire. At first step, we defined the 16 big data service models from interview with librarians, and LIS professions. Second step, it was considered necessity, timeliness, possibility of development. We developed the final two services called on 'Decision Support Services for Public Librarians' and 'Book Recommendation Services for Users.'

• Journal of the Korean Society for information Management
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• v.36 no.4
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• pp.183-205
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• 2019

Among the various methods for identifying users's information needs, Log analysis methods can realistically reflect the users' actual search behavior and analyze the overall usage of most users. Based on the large quantity of query log big data obtained through the portal service of the National Archives of Korea, this study conducted an analysis by the information type and search result type in order to identify the users' information needs. The Query log used in analysis were based on 1,571,547 query data collected over a total of 141 months from 2007 to December 2018, when the National Archives of Korea provided search services via the web. Furthermore, based on the analysis results, improvement methods were proposed to improve user search satisfaction. The results of this study could actually be used to improve and upgrade the National Archives of Korea search service.

• The Journal of Bigdata
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• v.9 no.1
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• pp.1-16
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• 2024

In urban design and planning, establishing neighborhood units and arranging urban planning facilities are important matters to be considered first. In particular, effective arrangement considering the influence area of each urban planning facility can solve traffic problems and improve the efficiency of urban structure according to the visitors to the facility, and can be used as basic data for more effective living areas. Therefore, this study proposed a methodology to analyze the number of users, the time required for access, and the destinations of users for major urban planning facilities such as schools and neighborhood parks based on mobile communication base station data. In addition, using this methodology, the users and influence areas of major urban planning facilities in Cheonan-si were analyzed.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.538-555
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• 2014

Systematic studies have been rarely conducted on the acceptance of big data technology despite the technology drawing much attention from academia, industry and general public. With big data technology still being in the infant stage in Korea, a study model was constructed in this paper by integrating the innovation diffusion theory and the task technology fit theory with this technology acceptance model (TAM) as the central framework to make big data technology more readily acceptable in the country, and the aim of making big data technology readily acceptable was expanded as the moderator variable of the TAM. The results of this study showed that "subjective norm" and "task technology fit" showed the most significant effect as the exogenous variables of the TAM. In addition, the "innovative characteristic of the organization" was the significant exogenous variable affecting the intention to accept big data technology to those "technology utilizers" that try to come up with new services or products that are technology-based; however, "subjective norm" was the rather significant factor affecting those simple "technology users". Finally, a significant difference was seen in the verification of mediation effect.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.247-249
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• 2015

본 논문에서는 하둡 플랫폼의 맵리듀스 모델에 기반하여 도서관 이용자들이 자주 대출하는 도서와 키워드 매칭을 통해 연관성이 높은 도서들을 추출하고 추천해 주는 도서 대출 추천 시스템을 구현 개발한다. 구현 개발된 시스템은 빅데이터의 특징을 갖는 도서관의 대출 로그 데이터로부터 타겟 도서와 유사한 키워드를 갖고 자주 대출되는 도서를 찾아 이용자에게 제공해 준다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1230-1233
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• 2013

스마트폰의 배급과 SNS의 성장으로 최근 데이터양은 급증하고 있다. IDC에 따르면 지난 10년간 생성된 데이터 보다 최근 2년 사이에 생성된 데이터양이 많은 걸로 나타났고 앞으로 점점 늘어날 것으로 예상된다. 이러한 대규모의 데이터인 빅데이터가 사회적 이슈가 되고 있고 이를 활용하려는 시도가 끊임없이 일어나고 있다. 본 논문에서는 빅데이터 상의 데이터 마이닝을 통하여 고객의 패턴을 분석하고 이용자에게 신뢰성 있는 데이터를 제공 할 수 있는 방안을 제시한다.