Abstract
We improve the state-of-the-art method for graph compression by exploiting the locality of reference observed in social network graphs. We take advantage of certain dense parts of those graphs, which enable us to further reduce the overall space requirements. The analysis and experimental evaluation of our method confirms our observations, as our results present improvements over a wide range of social network graphs. © 2014 Springer International Publishing Switzerland.
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CITATION STYLE
Liakos, P., Papakonstantinopoulou, K., & Sioutis, M. (2014). On the effect of locality in compressing social networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8416 LNCS, pp. 650–655). Springer Verlag. https://doi.org/10.1007/978-3-319-06028-6_71
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