DenseAlert: Incremental Dense-SubTensor Detection in Tensor Streams

DenseStream is an incremental algorithm for detecting dense subtensors in tensor streams, and DenseAlert is an incremental algorithm for spotting suddenly emerging dense subtensors. They have the following properties:

• Fast and 'Any Time': By maintaining and updating a dense subtensor, our algorithms detect a dense subtensor in a tensor stream significantly faster than batch algorithms.
• Provably Accurate: Our algorithms provide theoretical guarantees on their accuracy, and show high accuracy in practice.
• Effective: Our algorithms successfully identifies anomalies, such as bot activities, rating manipulations, and network intrusions, in real-world tensors.

Datasets

The download links for the datasets used in the paper are here

Building and Running DenseAlert

Please see User Guide

Running Demo

For demo, please type 'make'

Reference

If you use this code as part of any published research, please acknowledge the following paper.

@inproceedings{shin2017densealert,
  title={DenseAlert: Incremental Dense-SubTensor Detection in Tensor Streams},
  author={Shin, Kijung and Hooi, Bryan and Kim, Jisu and Faloutsos, Christos},
  booktitle={Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
  year={2017},
  pages={1057--1066},
  organization={ACM}
}