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Big data in complex systems = challenges and opportunities /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Big data in complex systems/ edited by Aboul Ella Hassanien ... [et al.].
Reminder of title:	challenges and opportunities /
other author:	Hassanien, Aboul Ella.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	viii, 499 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Big data. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-11056-1
ISBN:	9783319110561 (electronic bk.)

Big data in complex systems = challenges and opportunities /
Big data in complex systemschallenges and opportunities /[electronic resource] :edited by Aboul Ella Hassanien ... [et al.]. - Cham :Springer International Publishing :2015. - viii, 499 p. :ill., digital ;24 cm. - Studies in big data,v.92197-6503 ;. - Studies in big data ;v.1..

Cloud Computing Infrastructure for Massive Data: A Gigantic Task Ahead -- Big Data Movement: a Challenge in Data Processing -- Towards Robust Performance Guarantees for Models Learned from High-Dimensional Data -- Stream Clustering Algorithms: A Primer -- Cross Language Duplicate Record Detection in Big Data -- A Novel Hybridized Rough Set And Improved Harmony Search Based Feature Selection For Protein Sequence Classification -- Autonomic Discovery of News Evolvement in Twitter -- Hybrid Tolerance Rough Set based Intelligent Approaches for Social Tagging Systems -- Exploitation Of Healthcare Databases In Anesthesiology And Surgical Care For Comparing Comorbidity Indexes In Cholecystectomized Patients -- Sickness Absence And Record Linkage Using Primary Healthcare, Hospital And Occupational Databases -- Classification of ECG Cardiac Arrhythmias using Bijective Soft Set -- Semantic Geographic Space: from Big Data to Ecosystems of Data -- DNA Methylation Data Analysis and Visualizing in a Common Form of Breast Cancer -- Data Quality, Analytics, and Privacy in Big Data -- Search, analysis and visual comparison of massive and heterogeneous data: Application in the medical field -- Modified Soft Rough set based ECG signal Classification for Cardiac arrhythmias -- Towards a new architecture for the description and manipulation of large distributed data.

This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.

ISBN: 9783319110561 (electronic bk.)

Standard No.: 10.1007/978-3-319-11056-1doiSubjects--Topical Terms:

981821
Big data.

LC Class. No.: QA76.9.D32

Dewey Class. No.: 005.7

Big data in complex systems = challenges and opportunities /
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520 $a This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.
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