2006 · 246 citations · 16 references
ComputingComputer ScienceBig Data AnalyticsDatabasesKnowledge RepresentationGraph AlgorithmsGraph AnalyticsGraph LabelingQuery OptimizationQuery ProcessingConstant-time AlgorithmsGraph IndexingGraph QueryingGraph-based QueryingIndexingLabelingReachabilityXml Indexing
Graph reachability is fundamental to a wide range of applications, including XML indexing, geographic navigation, Internet routing, ontology queries based on RDF/OWL, etc. Many applications involve huge graphs and require fast answering of reachability queries. Several reachability labeling methods have been proposed for this purpose. They assign labels to the vertices, such that the reachability between any two vertices may be decided using their labels only. For sparse graphs, 2-hop based reachability labeling schemes answer reachability queries efficiently using relatively small label space. However, the labeling process itself is often too time consuming to be practical for large graphs. In this paper, we propose a novel labeling scheme for sparse graphs. Our scheme ensures that graph reachability queries can be answered in constant time. Furthermore, for sparse graphs, the complexity of the labeling process is almost linear, which makes our algorithm applicable to massive datasets. Analytical and experimental results show that our approach is much more efficient than stateof- the-art approaches. Furthermore, our labeling method also provides an alternative scheme to tradeoff query time for label space, which further benefits applications that use tree-like graphs.
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Computational prediction of human metabolic pathways from the complete human genome
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