MAT‐Index: An index for fast multiple aspect trajectory similarity measuring

The semantic enrichment of mobility data with several information sources has led to a new type movement data, the so-called multiple aspect trajectories. Comparing trajectories is crucial for analysis tasks such as querying, clustering, similarity, and classification. Multiple trajectory similarity measurement more complex computationally expensive, because large number heterogeneous aspects space, time, semantics that require different treatment. Only few works in literature focus on optimizing all these dimensions single solution, and, best our knowledge, none them proposes fast point-to-point comparison. In this article we propose Aspect Trajectory Index, an index structure comparison trajectories, considering its three basic semantics. Quantitative qualitative evaluations show processing time reduction up 98.1%.