• Paper: Mourad Khayati, Philippe Cudré-Mauroux, and Michael H. Böhlen: Scalable Recovery of Missing Blocks in Time Series with High and Low Cross-Correlations. KAIS 2020.
• Algorithms: The benchmark evaluates all the algorithms mentioned in the paper: CDRec, GROUSE, MRNN, SSA, STMVL, TKCM, and TRMF. To enable/disable any algorithm, please refer to the Algorithms customization section below.
• Datasets: The benchmark evaluates all the datasets used in the paper: gas (drfit6), gas (drfit10), baseball, meteo, tempretaure, and BAFU. To enable/disable any dataset, please refer to the Datasets customization section below.
• Scenarios: The benchmark will execute the full set of 15 recovery scenarios and report the error using RMSE, MSE and MAE. A detailed description of the recovery scenarios can be found here.

Prerequisites | Build | Execution | Parameterization | Citation

• Ubuntu 16 or Ubuntu 18 (including Ubuntu derivatives, e.g., Xubuntu) or the same distribution under WSL.
• Clone this repository.
• Mono: Install mono from https://www.mono-project.com/download/stable/ (takes few minutes).

• Build the Testing Framework using the installation script located in the root folder (takes several minutes):

    $ sh install_linux.sh

    $ cd TestingFramework/bin/Debug/
    $ mono TestingFramework.exe

• Results: All results will be added to Results folder. The accuracy results of all algorithms will be sequentially added for each scenario and dataset to: Results/.../.../.../error/. The runtime results of all algorithms will be added to: Results/.../.../.../runtime/. The plots of the recovered blocks will be added to the folder Results/.../.../.../plots/.

• Warning: The test suite with the default setup will take ~20 hours to finish and will produce up to 3GB of output files with all recovered data and plots unless stopped early.

To exclude an algorithm from the benchmark

• open the file TestingFramework/config.cfg
• add an entry IgnoreAlgorithms = and specify the list of algorithm codes to exclude them
• the line starting with #IgnoreAlgorithms = provides codes for all the algorithms in the benchmark

To add a dataset to the benchmark

• import the file to TestingFramework/bin/Debug/data/{name}/{name}_normal.txt
• • Requirements: >= 10 columns, >= 1'000 rows, column separator - empty space, row separator - newline
• add {name} to the list of datasets in TestingFramework/config.cfg

@article{DBLP:journals/kais/KhayatiCB20,
  author    = {Mourad Khayati and
               Philippe Cudr{\'{e}}{-}Mauroux and
               Michael H. B{\"{o}}hlen},
  title     = {Scalable recovery of missing blocks in time series with high and low
               cross-correlations},
  journal   = {Knowl. Inf. Syst.},
  volume    = {62},
  number    = {6},
  pages     = {2257--2280},
  year      = {2020},
  url       = {https://doi.org/10.1007/s10115-019-01421-7},
  doi       = {10.1007/s10115-019-01421-7},
  biburl    = {https://dblp.org/rec/journals/kais/KhayatiCB20.bib},
}