| 书目名称 | Integrity Constraints on Rich Data Types | | 编辑 | Shaoxu Song,Lei Chen | | 视频video | | | 概述 | Explores application of data dependencies and their extensions to big data analysis.Guides readers on selection of appropriate data dependencies based on expressive power and discovery cost.Identifies | | 丛书名称 | Synthesis Lectures on Data Management | | 图书封面 |  | | 描述 | This book examines the recent trend of extending data dependencies to adapt to rich data types in order to address variety and veracity issues in big data. Readers will be guided through the full range of rich data types where data dependencies have been successfully applied, including categorical data with equality relationships, heterogeneous data with similarity relationships, numerical data with order relationships, sequential data with timestamps, and graph data with complicated structures. The text will also discuss interesting constraints on ordering or similarity relationships contained in novel classes of data dependencies in addition to those in equality relationships, e.g., considered in functional dependencies (FDs). In addition to exploring the concepts of these data dependency notations, the book investigates the extension relationships between data dependencies, such as conditional functional dependencies (CFDs) that extend conventional functional dependencies (FDs). This forms in the book a family tree of extensions, mostly rooted in FDs, that help illuminate the expressive power of various data dependencies. Moreover, the book points to work on the discovery of dep | | 出版日期 | Book 2023 | | 关键词 | Data Dependencies; Ordered Data; Temporal Data; Graph Data; Function Dependencies | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-27177-9 | | isbn_softcover | 978-3-031-27179-3 | | isbn_ebook | 978-3-031-27177-9Series ISSN 2153-5418 Series E-ISSN 2153-5426 | | issn_series | 2153-5418 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 17:03:24
