Campusbibliothek

Pearls of algorithm engineering Paolo Ferragina

By: Contributor(s): Material type: TextTextLanguage: English Publisher: Cambridge New York Melbourne New Dehli Singapore Cambridge University Press 2023Description: xii, 305 Seiten Illustrationen, DiagrammeContent type:
  • Text
Media type:
  • ohne Hilfsmittel zu benutzen
Carrier type:
  • Band
ISBN:
  • 9781009123280
Subject(s): Additional physical formats: No titleDDC classification:
  • 005.13 23/eng/20230425
LOC classification:
  • QA76.9.A43
Other classification:
  • 54.52
Contents:
A warm-up! -- Random sampling -- List ranking -- Sorting atomic items -- Set intersection -- Sorting strings -- The dictionary problem -- Searching strings by prefix -- Searching strings by substring -- Integer coding -- Statistical coding -- Dictionary-based compressors -- The Burrows-Wheeler transform -- Compressed data structures.
Summary: "This book provides students, researchers and professionals working in big data applications with solutions to core algorithmic problems, analyzed within RAM and external-memory models of computation. Pseudocode and running examples deal with various data types, and algorithmic tools for sampling, sorting, search, and data compression are included"--
List(s) this item appears in: New Books 2026/2 January-February
Holdings
Item type Current library Collection Shelving location Call number Status Date due Barcode
Book Book Gebäude E1 4 (MPI-INF) MPI-INF (E1 4) Internal Ferragina (Browse shelf(Opens below)) restricted use 2000000389929
Book Book Gebäude E2 3 (UdS Campusbibliothek für Informatik und Mathematik) Campusbibliothek für Informatik und Mathematik (E2 3) Books A-Z (1st) FER p2 2023:1 1.Ex (Browse shelf(Opens below)) Available 2200000462640

LIteraturangaben

A warm-up! -- Random sampling -- List ranking -- Sorting atomic items -- Set intersection -- Sorting strings -- The dictionary problem -- Searching strings by prefix -- Searching strings by substring -- Integer coding -- Statistical coding -- Dictionary-based compressors -- The Burrows-Wheeler transform -- Compressed data structures.

"This book provides students, researchers and professionals working in big data applications with solutions to core algorithmic problems, analyzed within RAM and external-memory models of computation. Pseudocode and running examples deal with various data types, and algorithmic tools for sampling, sorting, search, and data compression are included"--

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