Fast and Compact Web Graph Representations
Compressed graph representations, in particular for Web graphs, have become an attractive research topic because of their applications in the manipulation of huge graphs in main memory. The state of the art is well represented by the WebGraph project, where advantage is taken of several particular properties of Web graphs to offer a trade-off between space and access time. In this paper we show that the same properties can be exploited with a different and elegant technique that builds on grammar-based compression. In particular, we focus on Re-Pair and on Ziv-Lempel compression, which, although cannot reach the best compression ratios of WebGraph, achievemuch faster navigation of the graph when both are tuned to use the same space. Moreover, the technique adapts well to run on secondary memory and in distributed scenarios. As a byproduct, we introduce an approximate Re-Pair version that works efficiently with severely limited main memory.
web graph compression algorithms experimentation performance data structures