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Research Article

Research Trend Analysis on Trajectory Data Mining: Focusing on Applications and Methods

궤적 데이터 마이닝 연구 동향: 응용 분야와 분석 방법론을 중심으로

김지연1, 이도현2, 이지윤3, 조주연4, 강영옥5

Jiyeon Kim1, Dohyun Lee2, Jiyoon Lee3, Juyeon Cho4, Youngok Kang5

1이화여자대학교 일반대학원 사회과교육과 지리학전공 박사과정
2이화여자대학교 일반대학원 사회과교육과 지리학전공 석사과정
3이화여자대학교 빅데이터분석학협동과정 석박사통합과정
4이화여자대학교 일반대학원 사회과교육과 지리학전공 석사과정
5이화여자대학교, 사회과교육과 교수
1Ph.D. Student, Department of Social Studies, Ewha Womans University
2Master Student, Department of Social Studies, Ewha Womans University
3Integrative Program, Department of Big Data Analytics, Ewha Womans University
4Master Student, Department of Social Studies, Ewha Womans University
5Professor, Department of Social Studies, Ewha Womans University
31 December 2022. pp. 37-57
PDF Citation
Abstract
With the recent development of technology to collect locations based on GPS and the explosion of devices equipped with GPS such as smartphones, an enormous amount of data related to the geographical location of moving objects such as people, vehicles, ships, and aircraft have been collected in real time. It has important academic and practical values related to the movement of things. Data mining methods for analyzing such data are also developing, and researchers are using trajectory data to explore the relationship between moving phenomena in cities and places that make up the city, suggesting solutions to various urban problems. As the trajectory can track the movement of various objects, so its application fields and purposes are also very diverse and it is widely used in areas such as urban planning, transportation, behavioral ecology, public safety, anomaly and violation detection, monitoring and so on. In particular, with the recent development of data mining methodology and deep learning technology, various analysis methods are fused to analyze trajectory data to derive meaningful research results, which requires systematic analysis. Under this background, this study classified about 150 domestic and foreign studies using trajectory data by application field and utilization methodology, and analyzed recent trends by application field and trajectory data analysis methodology. It is considered that this study can be used in the future to explore methodologies applicable to trajectory data, to explore specific cases related to trajectory data analysis, and to derive application services using trajectory data.
Keywords
Trajectory data
Trajectory data application field
Trajectory data mining
Trajectory prediction
Research trend analysis
최근 GPS에 기반한 위치 수집 기술의 발전과 스마트폰과 같은 GPS를 탑재한 디바이스의 폭발적인 증가로 사람, 차량, 선박, 항공체와 같은 움직이는 물체의 지리적 위치에 대한 엄청난 양의 데이터가 실시간으로 수집되고 있다. 이는 사물의 움직임과 관련된 중요한 학문적 및 실용적 가치를 가지고 있다. 이와 같은 데이터를 분석하기 위한 데이터 마이닝 방법 또한 함께 발전하고 있으며 연구자들은 궤적 데이터를 활용하여 도시에서 일어나는 이동 현상과 도시를 구성하는 장소 간의 관계 등을 탐색함으로써 다양한 도시 문제에 대한 해결방안을 제시하고 있다. 궤적은 다양한 물체의 움직임을 추적할 수 있는 만큼 그 활용 분야와 목적 역시 매우 다양하여 도시 계획, 교통, 행동생태학, 공공안전, 이상 및 위반 탐지, 감시 등과 같은 분야에서 널리 활용되고 있다. 특히 최근 데이터 마이닝 방법론과 딥러닝 기술의 발전으로 궤적 데이터 분석에 다양한 분석방법이 융합적으로 접목되어 의미 있는 연구결과 도출되고 있어 이에 대한 체계적 분석이 필요하다. 이러한 배경하에 본 연구는 궤적 데이터를 활용한 국내외 약 150여 편의 연구를 응용분야 및 활용방법론 별로 구분하고, 응용분야별, 궤적 데이터 분석 방법론별 최근 동향을 분석하였다. 이는 향후 궤적 데이터에 적용가능한 방법론 탐색, 궤적 데이터 분석과 관련된 구체적 사례 탐색, 궤적 데이터를 활용한 응용서비스 도출의 자료로 활용될 수 있을 것으로 사료된다.
키워드
궤적 데이터
궤적 데이터 응용 분야
궤적 데이터 마이닝
궤적 예측
연구 동향
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Information
  • Publisher :The Korean Cartographic Association
  • Publisher(Ko) :한국지도학회
  • Journal Title :Journal of the Korean Cartographic Association
  • Journal Title(Ko) :한국지도학회지
  • Volume : 22
  • No :3
  • Pages :37-57
  • DOI :https://doi.org/10.16879/jkca.2022.22.3.037
Journal Informaiton Journal of the Korean Cartographic Association Journal of the Korean Cartographic Association
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