ReVival is an online tool to recover missing blocks in batches and streams of time series using the Centroid Decomposition (CD) and to visualize the properties of the CD algorithm.

This tool was created at the eXascale Infolab, a research group in the University of Fribourg, Switzerland.

Centroid Decomposition

The Centroid Decomposition (CD) is a matrix decomposition technique that factorizes an input matrix X (consisting of multiple time-series as columns) into the product of two matrices L (loading matrix) and R (relevance matrix), such that X = L * RT. CD allows to efficiently perform recovery of missing values in large time series, both in batch mode and streaming mode. The batch recovery uses SSV algorithm introduced here. The streaming recovery uses an efficient incremental version of the CD algorithm.

In addition to the recovery, ReVival can be used as an online calculator to compute the Centroid Cecomposition and to visualize different sign vector maximization strategies that can be used by CD.

ReVival consists of the following components:


  • Ines Arous, Mourad Khayati, Philippe Cudré-Mauroux, Ying Zhang, Martin Kersten, and Svetlin Stalinlov. “RecovDB: Accurate and Efficient Missing Blocks Recovery for Large Time Series.” In 35th IEEE International Conference on Data Engineering (ICDE 2019). Macau, China, 2019.
  • Mourad Khayati, Michael H. Böhlen, and Johann Gamper. “Memory-Efficient Centroid Decomposition for Long Time Series.” In IEEE 30th International Conference on Data Engineering (ICDE 2014), Chicago, ICDE 2014, IL, USA, March 31 - April 4, 2014, 100–111, 2014.

Teams involved:


August 2018