Big Data, Data Mining and Data Science: Algorithms, Infrastructures, Management and Security

Book

Big Data, Data Mining and Data Science

Algorithms, Infrastructures, Management and Security

Edited by: George Dimitoglou , Leonidas Deligiannidis and Hamid R. Arabnia

Language: English

Published/Copyright: 2025

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This book is in the series

Volume 2 | Intelligent Computing

About this book

Through the application of cutting-edge techniques like Big Data, Data Mining, and Data Science, it is possible to extract insights from massive datasets. These methodologies are crucial in enabling informed decision-making and driving transformative advancements across many fields, industries, and domains. This book offers an overview of latest tools, methods and approaches while also highlighting their practical use through various applications and case studies.

Presents advances in Big Data, Data Mining, and Data Science research and applications.

Discusses novel algorithms, techniques, methodologies, infrastructures, frameworks, and privacy preservation.

Includes Real-world case studies and use cases.

Author / Editor information

G. Dimitoglou, Hood Coll.; L. Deligiannidis, W. Inst. of Tech, USA; H.R. Arabnia, U Georgia, Georgia.

Topics

Frontmatter Publicly Available Download PDF	I
Preface Publicly Available Download PDF	V
Contents Publicly Available Download PDF	VII
Methods and instrumentation
1 Identifying and estimating outliers in time series with nonstationary mean through multiobjective optimization method Koki Kyo Requires Authentication Unlicensed Licensed Download PDF	1
2 Using the intentionally linked entities (ILE) database system to create hypergraph databases with fast and reliable relationship linking, with example applications Vitit Kantabutra Requires Authentication Unlicensed Licensed Download PDF	21
3 Rapid and automated determination of cluster numbers for high-dimensional big data: a comprehensive update Zohreh Safari Requires Authentication Unlicensed Licensed Download PDF	37
4 Canonical correlation analysis and exploratory factor analysis of the four major centrality metrics Natarajan Meghanathan Requires Authentication Unlicensed Licensed Download PDF	49
5 Navigating the landscape of automated data preprocessing: an in-depth review of automated machine learning platforms Abderahim Salhi, Althea C. Henslee, James Ross, Joseph Jabour and Ian Dettwiller Requires Authentication Unlicensed Licensed Download PDF	71
6 Generating random XML Peter M. Maurer and John Carbone Requires Authentication Unlicensed Licensed Download PDF	83
Applications and case studies
7 Exploring autism risk: a deep dive into graph neural networks and gene interaction data Danushka Bandara and Kyle Riccardi Requires Authentication Unlicensed Licensed Download PDF	105
8 Leveraging ChatGPT and table arrangement techniques in advanced newspaper content analysis for stock insights Masaki Murata Requires Authentication Unlicensed Licensed Download PDF	121
9 An experimental study on road surface classification Addisson Salazar, Gonzalo Safont, Luis Vergara and Alberto Gonzalez Requires Authentication Unlicensed Licensed Download PDF	145
10 RNN models for evaluating financial indices: examining volatility and demand-supply shifts in financial markets during COVID-19 Ray R. Hashemi, Omid M. Ardakani, Jeffrey Young and Azita G. Bahrami Requires Authentication Unlicensed Licensed Download PDF	165
11 Topological methods for vibration feature extraction Dean Lee and Jamal Rorie Requires Authentication Unlicensed Licensed Download PDF	185
12 Dyna-SPECTS: DYNAmic enSemble of Price Elasticity Computation models using Thompson Sampling in e-commerce Srividhya Sethuraman, G. Uma, Sunny Kumar and Sharadha Ramanan Requires Authentication Unlicensed Licensed Download PDF	215
13 Creating a metadata schema for reservoirs of data: a systems engineering approach Barry C. White, Rachel E. Jordan, Reena R. Patel, LaKenya K. Walker and Matthew D. Bray Requires Authentication Unlicensed Licensed Download PDF	251
14 Implementation and evaluation of an eXplainable artificial intelligence to explain the evaluation of an assessment analytics algorithm for freetext exams in psychology courses in higher education to attest QBLM-based competencies Ramona Srbecky, Franz Bühler, Jörg Schuljak, Simon-Alexander Wetzel, Michael Winterhagen, Wieland Fraas, Jan Dettmers and Matthias Hemmje Requires Authentication Unlicensed Licensed Download PDF	271
15 Toward a skill-centered qualification ontology supporting data mining of human resources in knowledge-based enterprise process representations Adrian Vogler, Binh Vu, Tobias Vogel, Benjamin Gernhardt and Matthias Hemmje Requires Authentication Unlicensed Licensed Download PDF	307
Index Requires Authentication Unlicensed Licensed Download PDF	333

Publishing information

Pages and Images/Illustrations in book

eBook published on:

December 30, 2024

eBook ISBN:

9783111344553

Hardcover published on:

December 30, 2024

Hardcover ISBN:

9783111344072

Pages and Images/Illustrations in book

Front matter:

8

Main content:

340

Illustrations:

83

Coloured Illustrations:

35

Tables:

49

https://doi.org/10.1515/9783111344553

eBook ISBN: 9783111344553

Hardcover ISBN: 9783111344072

Keywords for this book

Big Data; Data Mining; Data Science; Big Data Management and Frameworks

Audience(s) for this book

Libraries, scholars, and professionals studying Big Data, Data Mining, and Data Science advancements and applications.

Safety & product resources

Manufacturer information:
Walter de Gruyter GmbH
Genthiner Straße 13
10785 Berlin
productsafety@degruyterbrill.com

Big Data, Data Mining and Data Science

Overview

About this book

Author / Editor information

Topics

Table of contents

Bibliographic data