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Handbook of Research on Big Data Clu...

García Márquez, Fausto Pedro,

Handbook of Research on Big Data Clustering and Machine Learning

Record Type:	Electronic resources : Monograph/item
Title/Author:	Handbook of Research on Big Data Clustering and Machine LearningFausto Pedro Garcia Marquez, editor.
other author:	García Márquez, Fausto Pedro,
Published:	Hershey, PA :Engineering Science Reference,2020.
Description:	1 online resource (xxi, 478 p.)
Subject:	Big dataHandbooks, manuals, etc.Research
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-0106-1
ISBN:	9781799801078 (ebk.)

Handbook of Research on Big Data Clustering and Machine Learning
Handbook of Research on Big Data Clustering and Machine Learning[electronic resource] /Fausto Pedro Garcia Marquez, editor. - Hershey, PA :Engineering Science Reference,2020. - 1 online resource (xxi, 478 p.)

Includes bibliographical references.

Technologies for handling big data / Rashmi Agrawal -- Evaluation of optimum and coherent economic-capital portfolios under complex market prospects / Mazin A. M. Al Janabi -- An overview of methodologies and challenges in sentiment analysis on social network / Aditya Salunkhe, Pallavi Chavan -- Big data analytics and models / Ferdi Sonmez, Mehmet Nazif Aydin, Ziya Nazim Perdahçi -- Analysis of gravitation based optimization algorithms for clustering and classification / Sajad Rather, Shanthi Bala P. -- A smart data application for the 5 Vs of big data in oil and gas industry / Kamaluddeen Usman Danyaro -- An optimised three dimensional clustering for microarray data / N. Narmadha, R. Rathipriya -- An overview of methodologies and challenges in sentiment analysis on social network / Pallavi Chavan, Aditya Salunke -- Analytics and machine learning for demand forecasting / William P. Fox, Anh Ninh -- Big data forensic analytics / Deepak Mane -- Call masking : a worrisome trend in Nigeria's telecommunications industry / Benjamin Enahoro Assay -- Clustering and Bayesian networks / Bhanu Chander -- Data-driven stochastic optimization for transportation road network design under uncertainty / Suh-Wen Chiou -- Designing recommender systems using big data technologies and machine learning algorithms / Partha Sarathi Chakraborty -- Digital fraud forensics with big data analytics / Muhammad Adeel Mannan, Iqbal Uddin Khan, Saboohi Mehmood, Aqeel-Ur-Rehman -- Examining visitors' characteristics and behaviors in tourist destinations through mobile phone users' location data / Masahide Yamamoto -- It's "crunch time" : exploring patterns of cross-purchases of fresh fruit and vegetables using machine learning techniques / Timofei Bogomolov, Malgorzata W. Korolkiewicz.

"This book examines the relationship between the analytic principles of clustering and machine learning to big data. It also explores the connection between engineering/technology and the organizational, administrative, and planning abilities of management"--

ISBN: 9781799801078 (ebk.)

LCCN: 2019016785Subjects--Topical Terms:

843697
Big data
--Research--Handbooks, manuals, etc.

LC Class. No.: QA76.9.B45 / A345 2020

Dewey Class. No.: 005.7

Handbook of Research on Big Data Clustering and Machine Learning
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020 $a 9781799801078 (ebk.)
020 $a 9781799801061 (hbk.)
035 $a 1091006374
040 $a LBSOR/DLC $b eng $c LBSOR $d DLC
050 0 0 $a QA76.9.B45 $b A345 2020
082 0 0 $a 005.7 $2 23
245 0 0 $a Handbook of Research on Big Data Clustering and Machine Learning $h [electronic resource] / $c Fausto Pedro Garcia Marquez, editor.
260 $a Hershey, PA : $b Engineering Science Reference, $c 2020.
300 $a 1 online resource (xxi, 478 p.)
504 $a Includes bibliographical references.
505 0 $a Technologies for handling big data / Rashmi Agrawal -- Evaluation of optimum and coherent economic-capital portfolios under complex market prospects / Mazin A. M. Al Janabi -- An overview of methodologies and challenges in sentiment analysis on social network / Aditya Salunkhe, Pallavi Chavan -- Big data analytics and models / Ferdi Sonmez, Mehmet Nazif Aydin, Ziya Nazim Perdahçi -- Analysis of gravitation based optimization algorithms for clustering and classification / Sajad Rather, Shanthi Bala P. -- A smart data application for the 5 Vs of big data in oil and gas industry / Kamaluddeen Usman Danyaro -- An optimised three dimensional clustering for microarray data / N. Narmadha, R. Rathipriya -- An overview of methodologies and challenges in sentiment analysis on social network / Pallavi Chavan, Aditya Salunke -- Analytics and machine learning for demand forecasting / William P. Fox, Anh Ninh -- Big data forensic analytics / Deepak Mane -- Call masking : a worrisome trend in Nigeria's telecommunications industry / Benjamin Enahoro Assay -- Clustering and Bayesian networks / Bhanu Chander -- Data-driven stochastic optimization for transportation road network design under uncertainty / Suh-Wen Chiou -- Designing recommender systems using big data technologies and machine learning algorithms / Partha Sarathi Chakraborty -- Digital fraud forensics with big data analytics / Muhammad Adeel Mannan, Iqbal Uddin Khan, Saboohi Mehmood, Aqeel-Ur-Rehman -- Examining visitors' characteristics and behaviors in tourist destinations through mobile phone users' location data / Masahide Yamamoto -- It's "crunch time" : exploring patterns of cross-purchases of fresh fruit and vegetables using machine learning techniques / Timofei Bogomolov, Malgorzata W. Korolkiewicz.
520 $a "This book examines the relationship between the analytic principles of clustering and machine learning to big data. It also explores the connection between engineering/technology and the organizational, administrative, and planning abilities of management"-- $c Provided by publisher.
650 0 $a Big data $x Research $v Handbooks, manuals, etc. $3 843697
650 0 $a Cluster analysis $x Research $v Handbooks, manuals, etc. $3 868263
650 0 $a Machine learning $x Research $v Handbooks, manuals, etc. $3 868264
700 1 $a García Márquez, Fausto Pedro, $e editor. $3 868262
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-0106-1