Fast and Multi-aspect Mining of Complex Time-stamped Event Streams-Reference-Cited by-同舟云学术

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

Published:2023-04-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2023
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Author:

Nakamura Kota¹^ORCID,Matsubara Yasuko¹^ORCID,Kawabata Koki¹^ORCID,Umeda Yuhei²^ORCID,Wada Yuichiro³^ORCID,Sakurai Yasushi¹^ORCID

Affiliation:

1. SANKEN, Osaka University, Japan

2. AI Lab., Fujitsu, Japan

3. AI Lab., Fujitsu, Japan and AIP, RIKEN, Japan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3543507.3583370

Reference88 articles.

1. [n.d.]. CIDDS (Coburg Intrusion Detection Data Sets). https://www.hs-coburg.de/forschung/forschungsprojekte-oeffentlich/informationstechnologie/cidds-coburg-intrusion-detection-data-sets.html [n.d.]. CIDDS (Coburg Intrusion Detection Data Sets). https://www.hs-coburg.de/forschung/forschungsprojekte-oeffentlich/informationstechnologie/cidds-coburg-intrusion-detection-data-sets.html

2. [n.d.]. Citi Bike Trip Histories. https://ride.citibikenyc.com/system-data [n.d.]. Citi Bike Trip Histories. https://ride.citibikenyc.com/system-data

3. [n.d.]. eCommerce purchase history from electronics store. https://www.kaggle.com/mkechinov/ecommerce-purchase-history-from-electronics-store [n.d.]. eCommerce purchase history from electronics store. https://www.kaggle.com/mkechinov/ecommerce-purchase-history-from-electronics-store

4. [n.d.]. eCommerce purchase history from jewelry store. https://www.kaggle.com/mkechinov/ecommerce-purchase-history-from-jewelry-store [n.d.]. eCommerce purchase history from jewelry store. https://www.kaggle.com/mkechinov/ecommerce-purchase-history-from-jewelry-store

5. [n.d.]. KDD Cup 1999 Data. http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html [n.d.]. KDD Cup 1999 Data. http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html

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