Detecting ‘Lifestates’ From Digital Footprint Time Series Data

Introduction & Background As digital footprints data continue to grow in complexity and volume, understanding and summarising large, high-dimensional time series is becoming increasingly important for analysing behavioural patterns. In various domains, mass data collection is routine and crucial to...

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Xehetasun bibliografikoak

Egile Nagusiak:	Sam Smith, Gavin Smith, John Harvey
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Swansea University 2025-10-01
Saila:	International Journal of Population Data Science
Gaiak:	Time Series Segmentation Clustering Change Point Detection Digital Footprints
Sarrera elektronikoa:	https://ijpds.org/article/view/3339
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