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Trajectory similarity search studies the problem of finding a trajectory from the database such the found trajectory most similar to the query trajectory. Past research mainly focused on two aspects: shape similarity search and semantic similarity search, leaving personalized similarity search untouched. In this paper, we propose a new query which takes user's preference into consideration to provide personalized searching. We define a new data model for this query and identify the efficiencydoi:10.1145/2346496.2346513 dblp:conf/kdd/WangL12 fatcat:scwfoycyuvesrjkjcvx7udzj4q