Screen LibraryData 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, pre...
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| Group Author: | |
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| Published: |
Springer,
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| Publisher Address: | Switzerland : |
| Publication Dates: | [2016] |
| Literature type: | Book |
| Language: | English |
| Subjects: | |
| Summary: |
"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." -- Publisher's description |
| Carrier Form: | xxi, 319 pages : illustrations, charts ; 25 cm |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9783319318592 3319318594 |
| Index Number: | QA76 |
| CLC: | TP311.13 |
| Call Number: | TP311.13/D232-33 |
| Contents: | An Interoperability Framework and Distributed Platform for Fast Data Applications / José Carlos Martins Delgado -- Complex Event Processing Framework for Big Data Applications / Rentachintala Bhargavi -- Agglomerative Approaches for Partitioning of Networks in Big Data Scenarios / Anupam Biswas [and others] -- Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs: A Big Data Perspective / Ying Xie, Jing (Selena) He, and Vijay V. Raghavan -- A Unified Approach to Data Modeling and Management in Big Data Era / Catalin Negru [and others] -- 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 [and others] -- 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. |