Data Science and Big Data Computing Frameworks and Methodologies by Zaigham Mahmood , Springer

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Springer Data Science and Big Data Computing Frameworks and Methodologies by Zaigham Mahmood

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._x000D_ Table of contents : - _x000D_ Part I: Data Science Applications and Scenarios_x000D_ _x000D_ _x000D_ _x000D_ An Interoperability Framework and Distributed Platform for Fast Data Applications_x000D_ Jose Carlos Martins Delgado_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ Complex Event Processing Framework for Big Data Applications_x000D_ Renta Chintala Bhargavi_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ Agglomerative Approaches for Partitioning of Networks in Big Data Scenarios_x000D_ Anupam Biswas, Gourav Arora, Gaurav Tiwari, Srijan Khare, Vyankatesh Agrawal and Bhaskar Biswas_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs: A Big Data Perspective_x000D_ Ying Xie, Jing (Selena) He and Vijay V. Raghavan_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ Part II: Big Data Modelling and Frameworks_x000D_ _x000D_ _x000D_ _x000D_ A Unified Approach to Data Modelling and Management in Big Data Era_x000D_ Catalin Negru, Florin Pop, Mariana Mocanu and Valentin Cristea_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ Interfacing Physical and Cyber Worlds: A Big Data Perspective_x000D_ Zartasha Baloch, Faisal Karim Shaikh and Mukhtiar A. Unar_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ Distributed Platforms and Cloud Services: Enabling Machine Learning for Big Data_x000D_ Daniel Pop, Gabriel Iuhasz and Dana Petcu_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ An Analytics Driven Approach to Identify Duplicate Bug Records in Large Data Repositories_x000D_ Anjaneyulu Pasala, Sarbendu Guha, Gopichand Agnihotram, Satya Prateek B and Srinivas Padmanabhuni_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ Part III: Big Data Tools and Analytics_x000D_ _x000D_ _x000D_ _x000D_ Large Scale Data Analytics Tools: Apache Hive, Pig and HBase_x000D_ N. Maheswari and M. Sivagami_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ Big Data Analytics: Enabling Technologies and Tools_x000D_ Mohanavadivu Periasamy and Pethuru Raj_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ A Framework for Data Mining and Knowledge Discovery in Cloud Computing_x000D_ Derya Birant and Pelin Yildirim_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ Feature Selection for Adaptive Decision Making in Big Data Analytics_x000D_ Jaya Sil and Asit Kumar Das_x000D_ _x000D_ _x000D_ _x000D_ _x000D_ _x000D_ Social Impact and Social Media Analysis Relating to Big DataNirmala Dorasamy and Natasa Pomazalova_x000D_