Description
Book SynopsisThis 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.
Trade Review“This title presents recent research and future trends in the area of big data. … It will be of value to students and researchers looking for research topics and to data scientists exploring ongoing work in the field of big data. Summing Up: Recommended. Graduate students; faculty and professionals.” (C. Tappert, Choice, Vol. 54 (7), March, 2017)
Table of ContentsPart I: Data Science Applications and Scenarios
An Interoperability Framework and Distributed Platform for Fast Data Applications
José Carlos Martins Delgado
Complex Event Processing Framework for Big Data Applications
Renta Chintala Bhargavi
Agglomerative Approaches for Partitioning of Networks in Big Data Scenarios
Anupam Biswas, Gourav Arora, Gaurav Tiwari, Srijan Khare, Vyankatesh Agrawal and Bhaskar Biswas
Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs: A Big Data Perspective
Ying Xie, Jing (Selena) He and Vijay V. Raghavan
Part II: Big Data Modelling and Frameworks
A Unified Approach to Data Modelling and Management in Big Data Era
Catalin Negru, Florin Pop, Mariana Mocanu and Valentin Cristea
Interfacing Physical and Cyber Worlds: A Big Data Perspective
Zartasha Baloch, Faisal Karim Shaikh and Mukhtiar A. Unar
Distributed Platforms and Cloud Services: Enabling Machine Learning for Big Data
Daniel Pop, Gabriel Iuhasz and Dana Petcu
An Analytics Driven Approach to Identify Duplicate Bug Records in Large Data Repositories
Anjaneyulu Pasala, Sarbendu Guha, Gopichand Agnihotram, Satya Prateek B and Srinivas Padmanabhuni
Part III: Big Data Tools and Analytics
Large Scale Data Analytics Tools: Apache Hive, Pig and HBase
N. Maheswari and M. Sivagami
Big Data Analytics: Enabling Technologies and Tools
Mohanavadivu Periasamy and Pethuru Raj
A Framework for Data Mining and Knowledge Discovery in Cloud Computing
Derya Birant and Pelin Yıldırım
Feature Selection for Adaptive Decision Making in Big Data Analytics
Jaya Sil and Asit Kumar Das
Social Impact and Social Media Analysis Relating to Big Data
Nirmala Dorasamy and Nataša Pomazalová
