A Survey on Methods and Systems for Graph Compression
arXiv:1504.00616
Abstract
We present an informal survey (meant to accompany another paper) on graph compression methods. We focus on lossless methods, briefly list available pproaches, and compare them where possible or give some indicators on their compression ratios. We also mention some relevant results from the field of lossy compression and algorithms specialized for the use on large graphs. --- Note: The comparison is by no means complete. This document is a first draft and will be updated and extended.
References in corpus (5)
- GraphLab: A New Framework For Parallel Machine Learning
- DAGGER: A Scalable Index for Reachability Queries in Large Dynamic Graphs
- GraphChi-DB: Simple Design for a Scalable Graph Database System -- on Just a PC
- Scalable RDF Data Compression using X10
- PReaCH: A Fast Lightweight Reachability Index using Pruning and Contraction Hierarchies