Cantitate/Preț
Produs
Total produse
Vezi coșul
Algorithms for Big Data: DFG Priority Program 1736 de Hannah Bast

Algorithms for Big Data: DFG Priority Program 1736: Lecture Notes in Computer Science, cartea 13201

Editat de Hannah Bast, Claudius Korzen, Ulrich Meyer, Manuel Penschuck
en Limba Engleză Paperback – 19 ian 2023
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.
Citește tot Restrânge

Din seria Lecture Notes in Computer Science

Preț: 28816 lei

Preț vechi: 36020 lei
-20% Nou

Puncte Express: 432
Preț estimativ în valută:
5516€ • 6009$ • 4628£

Carte tipărită la comandă

Livrare economică 19 decembrie 24 - 02 ianuarie 25

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783031215339
ISBN-10: 3031215338
Pagini: 285
Ilustrații: XIV, 285 p. 141 illus., 54 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.42 kg
Ediția:1st ed. 2022
Editura: Springer Nature Switzerland
Colecția Springer
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

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.

Recenzii

“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)

Textul de pe ultima copertă

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.

Caracteristici

This book is open access, which means that you have free and unlimited access Surveys the progress in selected aspects of the growing field of big data Tackles problems such as transportation systems, energy supply, medicine Examines in combination with increasingly complicated hardware