Min-wise independent permutations
Journal of Computer and System Sciences - 30th annual ACM symposium on theory of computing
A survey of graph layout problems
ACM Computing Surveys (CSUR)
Introduction to Algorithms
The Link Database: Fast Access to Graphs of the Web
DCC '02 Proceedings of the Data Compression Conference
Towards Compressing Web Graphs
DCC '01 Proceedings of the Data Compression Conference
Compressing the Graph Structure of the Web
DCC '01 Proceedings of the Data Compression Conference
The WebGraph Framework II: Codes For The World-Wide Web
DCC '04 Proceedings of the Conference on Data Compression
The webgraph framework I: compression techniques
Proceedings of the 13th international conference on World Wide Web
A scalable pattern mining approach to web graph compression with communities
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
On compressing social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 20th international conference on World wide web
On summarizing graph homogeneously
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications
Diversified ranking on large graphs: an optimization viewpoint
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
GBASE: a scalable and general graph management system
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Practical representations for web and social graphs
Proceedings of the 20th ACM international conference on Information and knowledge management
Query preserving graph compression
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Graph pattern matching revised for social network analysis
Proceedings of the 15th International Conference on Database Theory
gbase: an efficient analysis platform for large graphs
The VLDB Journal — The International Journal on Very Large Data Bases
On compressing weighted time-evolving graphs
Proceedings of the 21st ACM international conference on Information and knowledge management
Compressed representation of web and social networks via dense subgraphs
SPIRE'12 Proceedings of the 19th international conference on String Processing and Information Retrieval
TurboGraph: a fast parallel graph engine handling billion-scale graphs in a single PC
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Making queries tractable on big data with preprocessing: through the eyes of complexity theory
Proceedings of the VLDB Endowment
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Compressing social networks can substantially facilitate mining and advanced analysis of large social networks. Preferably, social networks should be compressed in a way that they still can be queried efficiently without decompression. Arguably, neighbor queries, which search for all neighbors of a query vertex, are the most essential operations on social networks. Can we compress social networks effectively in a neighbor query friendly manner, that is, neighbor queries still can be answered in sublinear time using the compression? In this paper, we develop an effective social network compression approach achieved by a novel Eulerian data structure using multi-position linearizations of directed graphs. Our method comes with a nontrivial theoretical bound on the compression rate. To the best of our knowledge, our approach is the first that can answer both out-neighbor and in-neighbor queries in sublinear time. An extensive empirical study on more than a dozen benchmark real data sets verifies our design.