On the use of social trajectory-based clustering methods for public transport optimization

Jordi Nin, David Carrera, Daniel Villatoro

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

1 Citació (Scopus)

Resum

Public transport optimisation is becoming everyday a more difficult and challenging task, because of the increasing number of transportation options as well as the increase of users. Many research contributions about this issue have been recently published under the umbrella of the smart cities research. In this work, we sketch a possible framework to optimize the tourist bus in the city of Barcelona. Our framework will extract information from Twitter and other web services, such as Foursquare to infer not only the most visited places in Barcelona, but also the trajectories and routes that tourist follow. After that, instead of using complex geospatial or trajectory clustering methods, we propose to use simpler clustering techniques as k-means or DBScan but using a real sequence of symbols as a distance measure to incorporate in theclustering process the trajectory information.

Idioma originalAnglès
Títol de la publicacióCitizen in Sensor Networks - 2nd International Workshop, CitiSens 2013, Revised Selected Papers
EditorsJordi Nin, Daniel Villatoro
EditorSpringer Verlag
Pàgines59-70
Nombre de pàgines12
ISBN (electrònic)9783319041773
DOIs
Estat de la publicacióPublicada - 2014
Publicat externament
Esdeveniment2nd International Workshop on Citizen in Sensor Networks, CitiSens 2013 - Barcelona, Spain
Durada: 19 de set. 201319 de set. 2013

Sèrie de publicacions

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volum8313
ISSN (imprès)0302-9743
ISSN (electrònic)1611-3349

Conferència

Conferència2nd International Workshop on Citizen in Sensor Networks, CitiSens 2013
País/TerritoriSpain
CiutatBarcelona
Període19/09/1319/09/13

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