Classification of traffic related short texts to analyse road problems in urban areas

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

The Volunteer Geographic Information (VGI) can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media’s publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.

Original languageEnglish
Pages (from-to)91-97
Number of pages7
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume42
Issue number4W3
DOIs
StatePublished - 25 Sep 2017
Event2nd International Conference on Smart Data and Smart Cities, UDMS 2017 - Puebla, Mexico
Duration: 4 Oct 20176 Oct 2017

Keywords

  • Classification
  • Data Analysis
  • Human sensors
  • Machine Learning
  • Traffic
  • Volunteered Geographic Information

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