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Band 13201

Algorithms for Big Data DFG Priority Program 1736

Aus der Reihe Lecture Notes in Computer Science

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Beschreibung

This open access book surveys the progress in addressing selected challenges related to the growth of big data in combination with increasingly complicated hardware.

It emerged from a research program established by the German Research Foundation (DFG) as priority program SPP 1736 on Algorithmics for...

Beschreibung

This open access book surveys the progress in addressing selected challenges related to the growth of big data in combination with increasingly complicated hardware.

It emerged from a research program established by the German Research Foundation (DFG) as priority program SPP 1736 on Algorithmics for Big Data where researchers from theoretical computer science worked together with application experts in order to tackle problems in domains such as networking, genomics research, and information retrieval. Such domains are unthinkable without substantial hardware and software support, and these systems acquire, process, exchange, and store data at an exponential rate.
The chapters of this volume summarize the results of projects realized within the program and survey-related work.

This is an open access book.

Rezension

“This book covers a wide range of topics in big data research. If I were running a master’s program in big data, I would use this book as a source for dissertations. It’s hard to envisage anyone (except perhaps a starting PhD student wanting to get a feel for the range of big data research) reading the entire book, but the individual papers will have their own readerships.” (J. H. Davenport, Computing Reviews, February 7, 2024)

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

19.01.2023
Abbildungen

XIV, 285 p. 141 illus., 54 illus. in color.
Herausgeber Hannah Bast + weitere

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

19.01.2023
Abbildungen

XIV, 285 p. 141 illus., 54 illus. in color.
Herausgeber
Verlag Springer
Seitenzahl

285
Maße (L/B/H)

23,5/15,5/1,7 cm
Gewicht

458 g
Auflage

1st ed. 2022
Sprache

Englisch
ISBN

978-3-031-21533-9
Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Algorithms for Big Data
  • Produktbild: Algorithms for Big Data

  • Algorithms for Large and Complex Networks Algorithms for Large-scale Network Analysis and the NetworKit Toolkit.- Generating Synthetic Graph Data from Random Network Models.- Sampling Efficiency for the Link Assessment Problem.- A Custom Hardware Architecture for the Link Assessment Problem.- Graph-based Methods for Rational Drug Design.- Recent Advances in Practical Data Reduction.- Skeleton-based Clustering by Quasi-Threshold Editing.- The Space Complexity of Undirected Graph Exploration.- Algorithms for Big Data and their Applications Scalable Cryptography.- Distributed Data Streams.- Energy-Efficient Scheduling.- The GENO Software Stack.- Laue Algorithms for Big Data Problems in de Novo Genome Assembly.- Scalable Text Index Construction. Big Data, Scalability, Algorithms, Applications, Graphs, Networks, Parallelism, Distributed, Memory Hierarchy, Algorithm Engineering, Network Analysis, Random Graphs, Graph Clustering, Data Streams, Cryptography, Energy Efficiency, Text Indices.