| 书目名称 | Data Science and Big Data Computing | | 副标题 | Frameworks and Metho | | 编辑 | Zaigham Mahmood | | 视频video | | | 概述 | Reviews the latest research and practice in data science and big data.Discusses tools and techniques for big data storage and analytics.Describes the frameworks relevant to data science, and their app | | 图书封面 |  | | 描述 | 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. | | 出版日期 | Book 2016 | | 关键词 | Big Data Modeling and Management; Data Mining and Predictive Analytics; Security, Privacy, Safety and | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-31861-5 | | isbn_softcover | 978-3-319-81139-0 | | isbn_ebook | 978-3-319-31861-5 | | copyright | Springer International Publishing Switzerland 2016 |
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发表于 2025-3-21 19:45:05
