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Published January 20, 2022 | Version v1
Journal article Open

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

  • 1. Federal University of Santa Catarina
  • 2. ISTI-CNR

Description

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

Notes

Funding: CAPES/PRINT process number 88887.310782/2018-00 Conselho Nacional de Desenvolvimento Cient ́ıfico e Tecnol ́ogico (CNPq), Funda ̧c ̃ao de Amparo a Pesquisa e Inova ̧c ̃ao do Estado de Santa Catarina (FAPESC) - Project Match - co-financing of H2020 Projects - Grant 2018TR 1266,

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Additional details

Funding

MASTER – Multiple ASpects TrajEctoRy management and analysis 777695
European Commission