Time works well: dynamic time warping based on time weighting for time series data mining

DOI10.1016/j.ins.2020.08.089zbMath1479.62075OpenAlexW3082288737MaRDI QIDQ2056315

Hailin Li

Publication date: 2 December 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.08.089

zbMATH Keywords

dynamic time warpingsimilarity measuretime series data miningfinancial stock analysistime weight

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Economic time series analysis (91B84)

Uses Software

• shapeDTW
• dtwSat
• GitHub
• SparseDTW

Cites Work

• Adaptive cost dynamic time warping distance in time series analysis for classification
• GARCH-based robust clustering of time series
• Partial multi-dividing ontology learning algorithm
• Time is money: dynamic-model-based time series data-mining for correlation analysis of commodity sales
• Time-series data mining
• Dynamic programming algorithm optimization for spoken word recognition

This page was built for publication: Time works well: dynamic time warping based on time weighting for time series data mining