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Traditionelles und Map-Reduce-basiertes Clustering für große Datenmengen: Eine systematische Überprüfung

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Description

Aufgrund des digitalen Fortschritts werden durch die modernen Anwendungen große Datenmengen erzeugt. Um die Daten in diesen großen Datenmengen genau zu kategorisieren, werden Clustering-Algorithmen verwendet. Dieses Buch enthält eine Literaturübersicht über verschiedene traditionelle Clustering-Algorithmen und ihre Vergleiche aus theoretischer Sicht. Das Buch gibt auch einen Überblick über die Anwendungen von Clustering-Techniken für I) Web-Log-Daten, II) Bilddaten und III) biologische Daten. Einer der Hauptnachteile der traditionellen Clustering-Algorithmen ist, dass sie bei zu großen Eingabedaten sehr rechenintensiv sind. Um dieses Problem zu überwinden, bieten wir auch eine umfassende Studie der neuesten MapReduce-basierten Clustering-Algorithmen, die das traditionelle Gegenstück mit dem Map-Reduce-Programmierparadigma erweitern. Dieses Buch ist vor allem für Forscher geeignet, die sich für die Entdeckung von Mustern in großen Datensätzen mithilfe von MapReduce-Clustering interessieren. Es hilft ihnen bei der Durchführung von Datenclustering in einer verteilten Umgebung. Noch wichtiger ist, dass die in diesem Buch diskutierten Themen und offenen Bereiche den Forschern helfen werden, ihre zukünftige Richtung zu bestimmen.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
14 June 2022
Listed Since
15 June 2022

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