Big-Data Analytics and Cloud Computing Theory, Algorithms and Applications [Hardcover]

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.

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