Data Science and Big Data Computing: Frameworks and Methodologies

This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.

Table of Contents

Part I: Data Science Applications and Scenarios
Chapter 1: An Interoperability Framework and Distributed Platform for Fast Data Applications
Chapter 2: Complex Event Processing Framework for Big Data Applications
Chapter 3: Agglomerative Approaches for Partitioning of Networks in Big Data Scenarios
Chapter 4: Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs: A Big Data Perspective

Part II: Big Data Modelling and Frameworks
Chapter 5: A Unified Approach to Data Modeling and Management in Big Data Era
Chapter 6: Interfacing Physical and Cyber Worlds: A Big Data Perspective
Chapter 7: Distributed Platforms and Cloud Services: Enabling Machine Learning for Big Data
Chapter 8: An Analytics-Driven Approach to Identify Duplicate Bug Records in Large Data Repositories

Part III: Big Data Tools and Analytics
Chapter 9: Large-Scale Data Analytics Tools: Apache Hive, Pig, and HBase
Chapter 10: Big Data Analytics: Enabling Technologies and Tools
Chapter 11: A Framework for Data Mining and Knowledge Discovery in Cloud Computing
Chapter 12: Feature Selection for Adaptive Decision Making in Big Data Analytics
Chapter 13: Social Impact and Social Media Analysis Relating to Big Data