\textsc{MasterMovelets}: discovering heterogeneous movelets for multiple aspect trajectory classification

DOI10.1007/s10618-020-00676-xzbMath1433.68339OpenAlexW3003713837MaRDI QIDQ1987181

Willian Zalewski, Lucas May Petry, Carlos Andres Ferrero, Vania Bogorny, Luis Otavio Alvares, Camila Leite da Silva

Publication date: 9 April 2020

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10618-020-00676-x

zbMATH Keywords

trajectory classificationmoveletsmultidimensional sequence classificationmultiple-aspect trajectoryrelevant subtrajectoriessemantic trajectory classification

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

MasterMovelets

Uses Software

• GitHub

Cites Work

• Time series shapelets: a novel technique that allows accurate, interpretable and fast classification
• Survey of multi-objective optimization methods for engineering
• On Finding the Maxima of a Set of Vectors

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