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
Storing and Querying Multiversion XML Documents using Durable Node Numbers
WISE '01 Proceedings of the Second International Conference on Web Information Systems Engineering (WISE'01) Volume 1 - Volume 1
Reachability and Distance Queries via 2-Hop Labels
SIAM Journal on Computing
Accelerating XPath evaluation in any RDBMS
ACM Transactions on Database Systems (TODS)
Dual Labeling: Answering Graph Reachability Queries in Constant Time
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Fast and practical indexing and querying of very large graphs
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
GRAIL: scalable reachability index for large graphs
Proceedings of the VLDB Endowment
Hi-index | 0.00 |
A time-evolving hierarchy (TEH) consists of multiple snapshots of the hierarchy (collection of one or more trees) as it evolves over time. It is often important to test reachability between a given pair of vertices in an arbitrary (possibly past) snapshot of the hierarchy. While interval-based indexing has been a popular strategy for reachability testing in static hierarchies, a straightforward extension of this strategy to TEHs is impractical because of the exorbitant indexing overheads. In this paper, we propose SCISSOR (selective snapshot indexing with progressive solution refinement), which, to the best of our knowledge is the first time and space efficient framework for answering reachability queries in TEHs. The main idea here is to maintain indexes only for a selective interspersed subset of TEH snapshots. A query on a non-indexed snapshot will be answered by utilizing the index of a temporally-nearby indexed snapshot and analyzing the structural changes that have occurred between the two snapshots. We also present a experimental study demonstrating the scalability and efficiency of the SCISSOR framework in terms of both indexing costs and query latencies.