LIDU : une approche basée sur la localisation pour l'identification de similarités d'intérêts entre utilisateurs dans les réseaux sociaux. (LIDU : Location-based approach to IDentify similar interests between Users in social networks)

Grâce aux technologies web et mobiles, le partage de donnees entre utilisateurs a considerablement augmente au cours des dernieres annees. Par exemple, les utilisateurs peuvent facilement enregistrer leurs trajectoires durant leurs deplacements quotidiens avec l'utilisation de recepteurs GPS et les mettre en relation avec les trajectoires d'autres utilisateurs. L'analyse des trajectoires des utilisateurs au fil du temps peut reveler des habitudes et preferences. Cette information peut etre utilisee pour recommander des contenus a des utilisateurs individuels ou a des groupes d'utilisateurs avec des trajectoires ou preferences similaires. En revanche, l'enregistrement de points GPS genere de grandes quantites de donnees. Par consequent, les algorithmes de clustering sont necessaires pour analyser efficacement ces donnees. Dans cette these, nous nous concentrons sur l'etude des differentes solutions pour analyser les trajectoires, extraire les preferences et identifier les interets similaires entre les utilisateurs. Nous proposons un algorithme de clustering de trajectoires GPS. En outre, nous proposons un algorithme de correlation basee sur les trajectoires des points proches entre deux ou plusieurs utilisateurs. Les resultats finaux ouvrent des perspectives interessantes pour explorer les applications des reseaux sociaux bases sur la localisation.

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