Imputation of Missing Boarding Stop Information in Smart Card Data with Machine Learning Methods

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the increase in population densities and environmental awareness, public transport has become an important aspect of urban life. Consequently, large quantities of transportation data are generated, and mining data from smart card use has become a standardized method to understand the travel habits of passengers. Increase in available data and computation power demands more sophisticated methods to analyze big data. Public transport datasets, however, often lack data integrity. Boarding stop information may be missing either due to imperfect acquirement processes or inadequate reporting. As a result, large quantities of observations and even complete sections of cities might be absent from the smart card database. We have developed a machine (supervised) learning method to impute missing boarding stops based on ordinal classification. In addition, we present a new metric, Pareto Accuracy, to evaluate algorithms where classes have an ordinal nature. Results are based on a case study in the city of Beer Sheva utilizing one month of data. We show that our proposed method significantly outperforms schedule-based imputation methods and can improve the accuracy and usefulness of large-scale transportation data. The implications for data imputation of smart card information is further discussed.

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, 2020, Proceedings
EditorsCesar Analide, Paulo Novais, David Camacho, Hujun Yin
PublisherSpringer Science and Business Media Deutschland GmbH
Pages17-27
Number of pages11
ISBN (Print)9783030623616
DOIs
StatePublished - 1 Jan 2020
Event21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020 - Guimaraes, Portugal
Duration: 4 Nov 20206 Nov 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12489 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020
Country/TerritoryPortugal
CityGuimaraes
Period4/11/206/11/20

Keywords

  • Boarding stop imputation
  • Machine learning
  • Smart card

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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