Introduction

Han Liu; Mihaela Cocea

doi:10.1007/978-3-319-70058-8_1

Introduction

Han Liu^*, Mihaela Cocea

^*Corresponding author for this work

School of Computing

Cardiff University

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Abstract

In this chapter, we will introduce the background of big data, in terms of five Vs, namely volume, velocity, variety, veracity and variability. The concepts of traditional data science are then explored to show the value of data. Furthermore, the concepts of machine learning and granular computing are provided in the context of intelligent data processing. Finally, the main contents of each of the following chapters are outlined.

Original language	English
Title of host publication	Granular Computing Based Machine Learning
Subtitle of host publication	A Big Data Processing Approach
Editors	Han Liu, Mihaela Cocea
Publisher	Springer Nature
Pages	1-10
Number of pages	10
ISBN (Electronic)	9783319700588
ISBN (Print)	9783319700571, 9783319888842
DOIs	https://doi.org/10.1007/978-3-319-70058-8_1
Publication status	Published - 23 Nov 2017

Publication series

Name	Studies in Big Data
Volume	35
ISSN (Print)	2197-6503
ISSN (Electronic)	2197-6511

Keywords

Conquer Approach
General Multi-task Learning
Granular Computing
Information Granules
Traditional Machine Learning

Access to Document

10.1007/978-3-319-70058-8_1

Cite this

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