Earticle

초록

영어

It is urgent to prepare countermeasures for traffic congestion problems of Korea's metropolitan area where central functions such as economic, social, cultural, and education are excessively concentrated. Most users of public transportation in metropolitan areas including Seoul use the traffic cards. If various information is extracted from traffic big data produced by the traffic cards, they can provide basic data for transport policies, land usages, or facility plans. Therefore, in this study, we extract valuable information such as the subway passengers' frequent travel patterns from the big traffic data provided by the Seoul Metropolitan Government Big Data Campus. For this, we use a Hadoop (High-Availability Distributed Object- Oriented Platform) to preprocess the big data and store it into a Mongo database in order to analyze it by a sequential pattern data mining technique. Since we analysis the actual big data, that is, the traffic cards' data provided by the Seoul Metropolitan Government Big Data Campus, the analyzed results can be used as an important referenced data when the Seoul government makes a plan about the metropolitan traffic policies.

목차

Abstract
 1. 서론
 2. 관련 연구
 3. 교통카드 빅데이터 전처리, 관리 및 분석
  3.1 교통카드 빅데이터
  3.2 교통카드 빅데이터 전처리 및 데이터베이스를 통한 관리
  3.3 교통카드 빅데이터 분석
 4. 교통카드 빅데이터 분석 결과
 5. 결론
 References

키워드

저자

• 김우생 [ Woosaeng Kim | Professor, Computer Software Department, Kwangwoon University ] Corresponding Author
• 김용훈 [ Yong Hoon Kim | Computer Software Department of Kwangwoon University ]
• 박희성 [ Hee-Sung Park | Computer Software Department of Kwangwoon University ]
• 박진규 [ Jin-Kyu Park | Computer Software Department of Kwangwoon University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  JITAM [Journal of Information Technology Applications and Management]

• 간기

  격월간

• pISSN

  1598-6284

• eISSN

  2508-1209

• 수록기간

  1999~2026

• 십진분류

  KDC 005 DDC 005