Big-Data Analytics and Cloud Computing: Theory, Algorithms and Applications

ISBN-13: 9783319253114 / Angielski / Twarda / 2016 / 169 str.

Marcello Trovati; Richard Hill; Ashiq Anjum

Opis

This book reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science. Topics and features: describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures; examines the applications and implementations that utilize big data in cloud architectures; surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions; identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches; provides relevant theoretical frameworks, empirical research findings, and numerous case studies; discusses real-world applications of algorithms and techniques to address the challenges of big datasets.

Spis treści

Part I: Theory

Data Quality Monitoring of Cloud Databases Based on Data Quality SLAs
Dimas C. Nascimento, Carlos Eduardo Pires and Demetrio Mestre

Role and Importance of Semantic Search in Big Data Governance
Kurt Englmeier

Multimedia Big Data: Content Analysis and Retrieval
Jer Hayes

An Overview of Some Theoretical Topological Aspects of Big Data
Marcello Trovati

Part II: Applications

Integrating Twitter Traffic Information with Kalman Filter Models for Public Transportation Vehicle Arrival Time Prediction
Ahmad Faisal Abidin, Mario Kolberg and Amir Hussain

Data Science and Big Data Analytics at CareerBuilder
Faizan Javed and Ferosh Jacob

Extraction of Bayesian Networks from Large Unstructured Datasets
Marcello Trovati

Two Case Studies Based on Large Unstructured Sets
Aaron Johnson, Paul Holmes, Lewis Craske, Marcello Trovati, Nik Bessis and Peter Larcombe

Information Extraction from Unstructured Datasets: An Application to Cardiac Arrhythmia Detection
Omar Behadada

A Platform for Analytics on Social Networks Derived from Organizational Calendar Data
Dominic Davies-Tagg, Ashiq Anjum and Richard Hill

O autorze

The editors are all members of the Computing and Mathematics Department at the University of Derby, UK, where Dr. Marcello Trovati serves as a Senior Lecturer in Mathematics, Dr. Richard Hill as a Professor and Head of the Computing and Mathematics Department, Dr. Ashiq Anjum as a Professor of Distributed Computing, Dr. Shao Ying Zhu as a Senior Lecturer in Computing, and Dr. Lu Liu as a Professor of Distributed Computing. The other publications of the editors include the Springer titles Guide to Security Assurance for Cloud Computing, Guide to Cloud Computing and Cloud Computing for Enterprise Architectures.

Blurb

This important and timely text/reference reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science.

Topics and features:

• Describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures
  
• Examines the applications and implementations that utilize big data in cloud architectures
  
• Surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions
  
• Identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches
  
• Provides relevant theoretical frameworks, empirical research findings, and numerous case studies
  
• Discusses real-world applications of algorithms and techniques to address the challenges of big datasets

This authoritative volume will be of great interest to researchers, enterprise architects, business analysts, IT infrastructure managers and application developers, who will benefit from the valuable insights offered into the adoption of architectures for big data and cloud computing. The work is also suitable as a textbook for university instructors, with the outline for a possible course structure suggested in the preface. 

The editors are all members of the Computing and Mathematics Department at the University of Derby, UK, where Dr. Marcello Trovati serves as a Senior Lecturer in Mathematics, Dr. Richard Hillas a Professor and Head of the Computing and Mathematics Department, Dr. Ashiq Anjum as a Professor of Distributed Computing, Dr. Shao Ying Zhu as a Senior Lecturer in Computing, and Dr. Lu Liu as a Professor of Distributed Computing. The other publications of the editors include the Springer titles Guide to Security Assurance for Cloud Computing, Guide to Cloud Computing and Cloud Computing for Enterprise Architectures.