Feature Selection in Conditional Random Fields for Map Matching of GPS Trajectories

Jian Yang, Liqiu Meng

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

12 Scopus citations

Abstract

Map matching of the GPS trajectory serves the purpose of recovering the original route on a road network from a sequence of noisy GPS observations. It is a fundamental technique to many Location Based Services. However, map matching of a low sampling rate on urban road network is still a challenging task. In this paper, the characteristics of Conditional Random Fields with regard to inducing many contextual features and feature selection are explored for the map matching of the GPS trajectories at a low sampling rate. Experiments on a taxi trajectory dataset show that our method may achieve competitive results along with the success of reducing model complexity for computation-limited applications.

Original languageEnglish
Title of host publicationProgress in Location-Based Services 2014
EditorsGeorg Gartner, Haosheng Huang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages121-135
Number of pages15
ISBN (Print)9783319118789
DOIs
StatePublished - 2015
Event11th International Symposium on Location Based Services, LBS 2014 - Vienna, Austria
Duration: 26 Nov 201428 Nov 2014

Publication series

NameLecture Notes in Geoinformation and Cartography
ISSN (Print)1863-2246
ISSN (Electronic)1863-2351

Conference

Conference11th International Symposium on Location Based Services, LBS 2014
Country/TerritoryAustria
CityVienna
Period26/11/1428/11/14

Keywords

  • Conditional random fields
  • Feature selection
  • GPS trajectory
  • Map matching

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