Variable-Length CliqueMotif (VLCM) finds frequently occurring patterns, so-called motifs, in a time series. It is the first exact algorithm that discovers latent motifs of variable length.
cd src/vlcm
mkdir build
cd build
cmake ..
cmake --build . --config Release
./VLCM <time-series-path> <window-min> <window-max> <correlation> [v]
cd src/ui
pip3 install -r requirements.txt
Alternatively, use a virtul environment:
python3 -m venv vlcm_venv/
source vlcm_venv/bin/activate
cd src/ui
python3 -m pip install -r requirements.txt
python3 app.py
[1] Linardi, Michele, et al. "Matrix Profile X: VALMOD - Scalable Discovery of Variable-Length Motifs in Data Series." Proceedings of the 2018 International Conference on Management of Data. 2018. Source: https://helios2.mi.parisdescartes.fr/~mlinardi/VALMOD.html
[2] Zimmerman, Zachary, et al. "Matrix Profile XIV: Scaling Time Series Motif Discovery with GPUs to Break a Quintillion Pairwise Comparisons a Day and Beyond." Proceedings of the ACM Symposium on Cloud Computing. 2019. Source: https://github.com/zpzim/SCAMP
[3] Jiang, Hua, Chu-Min Li, and Felip Manyà. "Combining Efficient Preprocessing and Incremental MaxSAT Reasoning for MaxClique in Large Graphs." Proceedings of the twenty-second European conference on artificial intelligence. 2016. Source: https://home.mis.u-picardie.fr/~cli/EnglishPage.html