Overview
D-Cube (
Disk-based
Dense-block
Detection) is an algorithm for detecting dense blocks in web-scale tensors.
D-Cube has the following properties:
- Scalable: D-Cube handles large data not fitting in memory or even on a disk.
- Fast: Even when data fit in memory, D-Cube outperforms its competitors in terms of speed.
- Accurate: D-Cube gives high accuracy in real-world data as well as theoretical accuracy guarantees.
Papers
D-Cube is described in the following papers:
-
D-Cube: Dense-Block Detection in Terabyte-Scale Tensors
Kijung Shin, Bryan Hooi, Jisu Kim, and Christos Faloutsos.
The 10th ACM International Conference on Web Search and Data Mining (WSDM) 2017, Cambridge, UK
[PDF] [Supplementary Document] [BIBTEX]
-
Out-of-Core and Distributed Algorithms for Dense Subtensor Mining (Longer ver.)
Kijung Shin, Bryan Hooi, Jisu Kim, and Christos Faloutsos.
[Arxiv]
Code
The source code used in the papers is available.
[ver.1 (WSDM)]
[ver.2 (TKDE)]
Datasets
People