Abstract

The need to run different kinds of algorithms over large Web graphs motivates the research for compressed graph representations that permit accessing without decompressing them. At this point there exist a few such compression proposals, some of them very effective in practice. In this paper we introduce a novel approach to graph compression, based on regarding the graph as a text and using existing techniques for text compression/indexing. This permits accessing the graph efficiently without decompressing it, and in addition brings in new functionalities over the compressed graph. Our experimental results show that our technique has the potential of being competitive with the best alternative techniques. 1 Introduction and Related Work Compression techniques aim at reducing the space requirement to store data. A recent exciting research area is that of compressed data structures. A compressed data structure uses little space, yet it can carry out the same operations of its classical (uncompressed) counterpart without the need

Citations