Data Science and Big Data Computing Frameworks and Methodologies /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Mahmood, Zaigham (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Θέματα: Computer science.; Computer communication systems.; Data mining.; Management information systems.; Computer Science.; Management of Computing and Information Systems.; Data Mining and Knowledge Discovery.; Computer Communication Networks.

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 an authoritative collection of thirty-six researchers and practitioners from around the world, discussing research developments an...

Πίνακας περιεχομένων:

• Part I: Data Science Applications and Scenarios
• An Interoperability Framework and Distributed Platform for Fast Data Applications
• Complex Event Processing Framework for Big Data Applications
• Agglomerative Approaches for Partitioning of Networks in Big Data Scenarios
• Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs: A Big Data Perspective
• Part II: Big Data Modelling and Frameworks
• A Unified Approach to Data Modelling and Management in Big Data Era
• Interfacing Physical and Cyber Worlds: A Big Data Perspective
• Distributed Platforms and Cloud Services: Enabling Machine Learning for Big Data
• An Analytics Driven Approach to Identify Duplicate Bug Records in Large Data Repositories
• Part III: Big Data Tools and Analytics
• Large Scale Data Analytics Tools: Apache Hive, Pig and HBase
• Big Data Analytics: Enabling Technologies and Tools
• A Framework for Data Mining and Knowledge Discovery in Cloud Computing
• Feature Selection for Adaptive Decision Making in Big Data Analytics
• Social Impact and Social Media Analysis Relating to Big Data.