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Mining frequent spatio-temporal patterns from location based social networks

Autor
Bejar, J.
Tipus d'activitat
Document cientificotècnic
Data
2014-10-09
Projecte finançador
SUstainable and PERsuasive Human Users moBility in future cities
Repositori
http://hdl.handle.net/2117/24313 Obrir en finestra nova
Resum
Location Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-temporal behavior. These social network provide a low rate sampling of user's location information during large intervals of time that can be used to discover complex behaviors, including frequent routes, points of interest or unusual events. This information is important for different domains like route planning, touristic recommendation systems or city planning. Other approaches have used the dat...
Citació
Béjar, J. "Mining frequent spatio-temporal patterns from location based social networks". 2014.
Paraules clau
Location Based, Frequent Itemsets, Smart Cities, User Profiles
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
KEMLG - Grup d´Enginyeria del Coneixement i Aprenentatge Automàtic

Participants

Arxius