M-Zoom / M-Biz

M-Zoom (Multidimensional Zoom) and M-Biz (Multidimensional Bi-directional Zoom) are algorithms for detecting dense subtensors. They have the following properties:

• scalable: scales almost linearly with all input factors
• provably accurate: provides high accuracy in real data as well as theoretical guarantees
• flexible: supports high-order tensors, various density measures, multi-subtensor detection, and size bounds

Datasets

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

Building and Running M-Zoom / M-Biz

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 papers.

@inproceedings{shin2016mzoom,
  author    = {Kijung Shin and Bryan Hooi and Christos Faloutsos},
  title     = {M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees},
  booktitle = {Joint European Conference on Machine Learning and Knowledge Discovery in Databases},
  pages     = {264--280},
  year      = {2016},
  url       = {http://dx.doi.org/10.1007/978-3-319-46128-1_17},
  doi       = {10.1007/978-3-319-46128-1_17},
  publisher = {Springer}
}

@article{shin2018mbiz,
  author    = {Kijung Shin and Bryan Hooi and Christos Faloutsos},
  title     = {Fast, Accurate and Flexible Algorithms for Dense Subtensor Mining},
  journal   = {ACM Transactions on Knowledge Discovery from Data (TKDD)},
  volume    = {12},
  number    = {3},
  pages     = {28:1--28:30},
  year      = {2018},
  url       = {http://dx.doi.org/10.1145/3154414},
  doi       = {10.1145/3154414},
  publisher = {ACM}
}