Efficient access to temporally overlaying spatial and textual trajectories

In this paper we deal with the problem of querying heterogeneous trajectory data consisting of spatial and textual trajectories defined over continuous temporal domains. In contrast with spatial trajectories, which describe the continuous movement in space of an individual, the textual trajectories of concern in this work describe the individual’s step-wise changing behavior, such as the transportation means used and the activities performed in a time period. Accessing large datasets of temporally aligned spatial and textual trajectories can provide valuable information on where certain behaviors take place. In this paper we present a novel index framework, called IRWI, for the efficient processing of queries on aligned spatio-textual trajectories formulated as sequences of ordered spatio-textual range queries q = q1, .., qn (sequenced queries). IRWI consists of a hybrid, spatial and textual, index data structure, enriched with a number of features that facilitate the early pruning of trajectories during the concurrent evaluation of the sub-queries q1, .., qn. As a result, the IRWI tree can be traversed only once. The experiments, conducted on both synthetic and real datasets, show a gain in performance with respect to state-of-the art techniques that increases significantly with the length of the query sequence.