Efficient management of transitive relationships in large data and knowledge bases
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Transitive closure algorithms based on graph traversal
ACM Transactions on Database Systems (TODS)
An efficient transitive closure algorithm for cyclic digraphs
Information Processing Letters
Precise interprocedural dataflow analysis via graph reachability
POPL '95 Proceedings of the 22nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Program analysis via graph reachability
ILPS '97 Proceedings of the 1997 international symposium on Logic programming
Journal of the ACM (JACM)
Communications of the ACM
Transitive closure algorithm MEMTC and its performance analysis
Discrete Applied Mathematics
Reachability and distance queries via 2-hop labels
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Direct Algorithms for Computing the Transitive Closure of Database Relations
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Optimizing bitmap indices with efficient compression
ACM Transactions on Database Systems (TODS)
Efficiently answering reachability queries on very large directed graphs
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
A Uniform Framework for Ad-Hoc Indexes to Answer Reachability Queries on Large Graphs
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
A Uniform Framework for Ad-Hoc Indexes to Answer Reachability Queries on Large Graphs
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
3-HOP: a high-compression indexing scheme for reachability query
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Query preserving graph compression
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
SCARAB: scaling reachability computation on large graphs
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
I/O cost minimization: reachability queries processing over massive graphs
Proceedings of the 15th International Conference on Extending Database Technology
Labeling workflow views with fine-grained dependencies
Proceedings of the VLDB Endowment
K-reach: who is in your small world
Proceedings of the VLDB Endowment
The exact distance to destination in undirected world
The VLDB Journal — The International Journal on Very Large Data Bases
TF-Label: a topological-folding labeling scheme for reachability querying in a large graph
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Computing weight constraint reachability in large networks
The VLDB Journal — The International Journal on Very Large Data Bases
Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Simple, fast, and scalable reachability oracle
Proceedings of the VLDB Endowment
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When answering many reachability queries on a large graph, the principal challenge is to represent the transitive closure of the graph compactly, while still allowing fast membership tests on that transitive closure. Recent attempts to address this problem are complex data structures and algorithms such as Path-Tree and 3-HOP. We propose a simple alternative based on a novel form of bit-vector compression. Our starting point is the observation that when computing the transitive closure, reachable vertices tend to cluster together. We adapt the well-known scheme of word-aligned hybrid compression (WAH) to work more efficiently by introducing word partitions. We prove that the resulting scheme leads to a more compact data structure than its closest competitor, namely interval lists. In extensive and detailed experiments, this is confirmed in practice. We also demonstrate that the new technique can handle much larger graphs than alternative algorithms.