Details

Autor(en) / Beteiligte

• Nguyen, Tuan
• Meger, Nicolas
• Rigotti, Christophe
• Pothier, Catherine
• Gourmelen, Noel
• Trouve, Emmanuel

Titel

A Pattern-Based Mining System for Exploring Displacement Field Time Series

Ist Teil von

• 2019 International Conference on Data Mining Workshops (ICDMW), 2019, p.1110-1113

Ort / Verlag

IEEE

Erscheinungsjahr

2019

Link zum Volltext

• IEEE_Xplore

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• This paper presents the first available system for mining patterns from Displacement Field Time Series (DFTS) along with the confidence measures inherent to these series. It consists of four main modules for data preprocessing, pattern extraction, pattern ranking and pattern visualization. It is based on an efficient extraction of reliable grouped frequent sequential patterns and on swap randomization. It can be for example used to assess climate change impacts on glacier dynamics.