Topics and features:
- Reviews a framework for fast data applications, a technique for complex event processing, and a selection of agglomerative approaches for partitioning of networks
- Discusses a big data approach to identifying minimum-sized influential vertices from large-scale weighted graphs
- Introduces a unified approach to data modeling and management, and offers a distributed computing perspective on interfacing physical and cyber worlds
- Presents techniques for machine learning in the context of big data, and describes an analytics-driven approach to identifying duplicate records in large data repositories
- Examines various enabling technologies and tools for data mining, including Apache Hadoop
- Proposes a novel framework for data extraction and knowledge discovery, and provides case studies on adaptive decision making and social media analysis
This comprehensive volume is a valuable reference for researchers, lecturers and students interested in data science and big data, in addition to professionals seeking to adopt the latest approaches in data analytics to gain business intelligence for strategic decision-making.
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