Analysis of Sparse Trajectory Features Based on Mobile Device Location for User Group Classification Using Gaussian Mixture Model

Location data collected from mobile devices via global positioning system often lack semantic information and can form sparse trajectories in space and time. This study investigates whether user age groups can be accurately classified solely from such sparse spatial–temporal trajectories. We propose...

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Autors principals:	Yohei Kakimoto, Yuto Omae, Hirotaka Takahashi
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2025-01-01
Col·lecció:	Applied Sciences
Matèries:	sparse trajectory classification mobile device location Gaussian mixture model machine learning
Accés en línia:	https://www.mdpi.com/2076-3417/15/2/982
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