IEICE TRANSACTIONS on Information
Urban Zone Discovery from Smart Card-Based Transit Logs
Summary :
Smart card payment systems provide a convenient billing mechanism for public transportation providers and passengers. In this paper, a smart card-based transit log is used to reveal functionally related regions in a city, which are called zones. To discover significant zones based on the transit log data, two algorithms, minimum spanning trees and agglomerative hierarchical clustering, are extended by considering the additional factors of geographical distance and adjacency. The hierarchical spatial geocoding system, called Geohash, is adopted to merge nearby bus stops to a region before zone discovery. We identify different urban zones that contain functionally interrelated regions based on passenger trip data stored in the smart card-based transit log by manipulating the level of abstraction and the adjustment parameters.
- Publication
- IEICE TRANSACTIONS on Information Vol.E100-D No.10 pp.2465-2469
- Publication Date
- 2017/10/01
- Publicized
- 2017/07/21
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2016OFL0004
- Type of Manuscript
- Special Section LETTER (Special Section on Advanced Log Processing and Office Information Systems)
- Category
Authors
Jae-Yoon JUNG
Kyung Hee University
Gyunyoung HEO
Kyung Hee University
Kyuhyup OH
Kyung Hee University
Keyword
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Jae-Yoon JUNG, Gyunyoung HEO, Kyuhyup OH, "Urban Zone Discovery from Smart Card-Based Transit Logs" in IEICE TRANSACTIONS on Information,
vol. E100-D, no. 10, pp. 2465-2469, October 2017, doi: 10.1587/transinf.2016OFL0004.
Abstract: Smart card payment systems provide a convenient billing mechanism for public transportation providers and passengers. In this paper, a smart card-based transit log is used to reveal functionally related regions in a city, which are called zones. To discover significant zones based on the transit log data, two algorithms, minimum spanning trees and agglomerative hierarchical clustering, are extended by considering the additional factors of geographical distance and adjacency. The hierarchical spatial geocoding system, called Geohash, is adopted to merge nearby bus stops to a region before zone discovery. We identify different urban zones that contain functionally interrelated regions based on passenger trip data stored in the smart card-based transit log by manipulating the level of abstraction and the adjustment parameters.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2016OFL0004/_p
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@ARTICLE{e100-d_10_2465,
author={Jae-Yoon JUNG, Gyunyoung HEO, Kyuhyup OH, },
journal={IEICE TRANSACTIONS on Information},
title={Urban Zone Discovery from Smart Card-Based Transit Logs},
year={2017},
volume={E100-D},
number={10},
pages={2465-2469},
abstract={Smart card payment systems provide a convenient billing mechanism for public transportation providers and passengers. In this paper, a smart card-based transit log is used to reveal functionally related regions in a city, which are called zones. To discover significant zones based on the transit log data, two algorithms, minimum spanning trees and agglomerative hierarchical clustering, are extended by considering the additional factors of geographical distance and adjacency. The hierarchical spatial geocoding system, called Geohash, is adopted to merge nearby bus stops to a region before zone discovery. We identify different urban zones that contain functionally interrelated regions based on passenger trip data stored in the smart card-based transit log by manipulating the level of abstraction and the adjustment parameters.},
keywords={},
doi={10.1587/transinf.2016OFL0004},
ISSN={1745-1361},
month={October},}
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TY - JOUR
TI - Urban Zone Discovery from Smart Card-Based Transit Logs
T2 - IEICE TRANSACTIONS on Information
SP - 2465
EP - 2469
AU - Jae-Yoon JUNG
AU - Gyunyoung HEO
AU - Kyuhyup OH
PY - 2017
DO - 10.1587/transinf.2016OFL0004
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E100-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2017
AB - Smart card payment systems provide a convenient billing mechanism for public transportation providers and passengers. In this paper, a smart card-based transit log is used to reveal functionally related regions in a city, which are called zones. To discover significant zones based on the transit log data, two algorithms, minimum spanning trees and agglomerative hierarchical clustering, are extended by considering the additional factors of geographical distance and adjacency. The hierarchical spatial geocoding system, called Geohash, is adopted to merge nearby bus stops to a region before zone discovery. We identify different urban zones that contain functionally interrelated regions based on passenger trip data stored in the smart card-based transit log by manipulating the level of abstraction and the adjustment parameters.
ER -
English
