/CubeScope

Fast and Multi-aspect Mining of Complex Time-stamped Event Streams (WWW23)

Primary LanguagePython

CubeScope

Implementation of CubeScope, Kota Nakamura, Yasuko Matsubara, Koki Kawabata, Yuhei Umeda, Yuichiro Wada, Yasushi Sakurai. The Web Conference 2023, WWW'23.

CubeScope is freely available for non-commercial purposes. If you intend to use CubeScope for a commercial purpose, please contact us by email at [kota88@sanken.osaka-u.ac.jp]

Quick demo

# Quick demo: Temporal clustering
# (Please see Section 5.2 "Q2 Accuracy" in this paper)  
$ sh demo.sh

Input for CubeScope

Pandas.DataFrame
Time + Multiple categorical attributes

0| Time | Attribute1 | Attribute2 | Attribute3 | Attribute4 | ...
1| :
2| :
3| :

Datasets

  1. NYC-Taxi
    https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page.
  2. Bike-Share
    https://ride.citibikenyc.com/system-data.
  3. Jewerly
    https://www.kaggle.com/mkechinov/ecommerce-purchase-history-from-jewelry-store.
  4. Electronics
    https://www.kaggle.com/mkechinov/ecommerce-purchase-history-from-electronics-store.
  5. AirForce
    http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html
  6. External
    https://www.hs-coburg.de/forschung/forschungsprojekte-oeffentlich/informationstechnologie/cidds-coburg-intrusion-detection-data-sets.html
  7. OpenStack
    ditto
  8. Kyoto
    https://www.takakura.com/Kyoto_data/

Citation

If you use this code for your research, please consider citing our WWW paper.

@inproceedings{nakamura2023cubescope,
  title={Fast and Multi-aspect Mining of Complex Time-stamped Event Streams},
  author={Nakamura, Kota and Matsubara, Yasuko and Kawabata, Koki and Umeda, Yuhei and Wada, Yuichiro and Sakurai, Yasushi},
  booktitle={Proceedings of the ACM Web Conference 2023},
  pages={1638--1649},
  year={2023}
}

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