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: Temporal clustering
# (Please see Section 5.2 "Q2 Accuracy" in this paper)
$ sh demo.sh
Pandas.DataFrame
Time + Multiple categorical attributes
0| Time | Attribute1 | Attribute2 | Attribute3 | Attribute4 | ...
1| :
2| :
3| :
- NYC-Taxi
https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page. - Bike-Share
https://ride.citibikenyc.com/system-data. - Jewerly
https://www.kaggle.com/mkechinov/ecommerce-purchase-history-from-jewelry-store. - Electronics
https://www.kaggle.com/mkechinov/ecommerce-purchase-history-from-electronics-store. - AirForce
http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html - External
https://www.hs-coburg.de/forschung/forschungsprojekte-oeffentlich/informationstechnologie/cidds-coburg-intrusion-detection-data-sets.html - OpenStack
ditto - Kyoto
https://www.takakura.com/Kyoto_data/
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}
}