Large-scale Graph Analysis: System, Algorithm and Optimization / / by Yingxia Shao, Bin Cui, Lei Chen
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| Autore: |
Shao Yingxia
|
| Titolo: |
Large-scale Graph Analysis: System, Algorithm and Optimization / / by Yingxia Shao, Bin Cui, Lei Chen
|
| Pubblicazione: | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Edizione: | 1st ed. 2020. |
| Descrizione fisica: | 1 online resource (XIII, 146 p. 78 illus., 30 illus. in color.) |
| Disciplina: | 511.5 |
| Soggetto topico: | Big data |
| Data mining | |
| Physics | |
| Management information systems | |
| Computer science | |
| Big Data | |
| Data Mining and Knowledge Discovery | |
| Applications of Graph Theory and Complex Networks | |
| Management of Computing and Information Systems | |
| Persona (resp. second.): | CuiBin |
| ChenLei | |
| Nota di bibliografia: | Includes bibliographical references. |
| Nota di contenuto: | 1. 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. |
| Sommario/riassunto: | This 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. |
| Titolo autorizzato: | Large-scale Graph Analysis: System, Algorithm and Optimization |
| ISBN: | 981-15-3928-6 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910413448203321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |
Serie:
Big Data Management, . 2522-0179