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Communication Dans Un Congrès Année : 2012

Clustering User Trajectories to Find Patterns for Social Interaction Applications

Résumé

Sharing of user data has substantially increased over the past few years facilitated by sophisticated Web and mobile applications, including social networks. For instance, users can easily register their trajectories over time based on their daily trips captured with GPS receivers as well as share and relate them with trajectories of other users. Analyzing user trajectories over time can reveal habits and preferences. This information can be used to recommend content to single users or to group users together based on similar trajectories and/or preferences. Recording GPS tracks generates very large amounts of data. Therefore clustering algorithms are required to efficiently analyze such data. In this paper, we focus on investigating ways of efficiently analyzing user trajectories and extracting user preferences from them. We demonstrate an algorithm for clustering user GPS trajectories. In addition, we propose an algorithm to correlate trajectories based on near points between two or more users. The obtained results provided interesting avenues for exploring Location-based Social Network (LBSN) applications.
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Dates et versions

hal-00868685 , version 1 (01-10-2013)

Identifiants

Citer

Reinaldo Bezerra Braga, Ali Tahir, Michela Bertolotto, Hervé Martin. Clustering User Trajectories to Find Patterns for Social Interaction Applications. W2GIS 2012 - 11th International Symposium on Web and Wireless Geographical Information Systems, Apr 2012, Naples, Italy. pp.82-97, ⟨10.1007/978-3-642-29247-7_8⟩. ⟨hal-00868685⟩
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