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010   $a981-15-3928-6
024 7 $a10.1007/978-981-15-3928-2
035   $a(CKB)4100000011325689
035   $a(DE-He213)978-981-15-3928-2
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035   $a(PPN)258872926
035   $a(EXLCZ)994100000011325689
100   $a20200701d2020      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aLarge-scale Graph Analysis: System, Algorithm and Optimization /$fby Yingxia Shao, Bin Cui, Lei Chen
205   $a1st ed. 2020.
210  1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2020.
215   $a1 online resource (XIII, 146 p. 78 illus., 30 illus. in color.) 
225 1 $aBig Data Management,$x2522-0179
311   $a981-15-3927-8 
320   $aIncludes bibliographical references.
327   $a1. Introduction -- 2. Graph Computing Systems for Large-Scale Graph Analysis -- 3. Partition-Aware Graph Computing System -- 4. Efficient Parallel Subgraph Enumeration -- 5. Efficient Parallel Graph Extraction -- 6. Efficient Parallel Cohesive Subgraph Detection -- 7. Conclusions.
330   $aThis book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms ? the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology for designing efficient large-scale graph algorithms.
410  0$aBig Data Management,$x2522-0179
606   $aBig data
606   $aData mining
606   $aPhysics
606   $aManagement information systems
606   $aComputer science
606   $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120
606   $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030
606   $aApplications of Graph Theory and Complex Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/P33010
606   $aManagement of Computing and Information Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I24067
615  0$aBig data.
615  0$aData mining.
615  0$aPhysics.
615  0$aManagement information systems.
615  0$aComputer science.
615 14$aBig Data.
615 24$aData Mining and Knowledge Discovery.
615 24$aApplications of Graph Theory and Complex Networks.
615 24$aManagement of Computing and Information Systems.
676   $a511.5
700   $aShao$b Yingxia$4aut$4http://id.loc.gov/vocabulary/relators/aut$0894269
702   $aCui$b Bin$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aChen$b Lei$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
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906   $aBOOK
912   $a9910413448203321
996   $aLarge-scale Graph Analysis: System, Algorithm and Optimization$91997622
997   $aUNINA