Название: Integrity Constraints on Rich Data TypesАвтор: Shaoxu Song, Lei Chen
Издательство: Springer
Год: 2023
Страниц: 154
Язык: английский
Формат: pdf (true), epub
Размер: 12.4 MB
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). Graph data have been widely observed in real-world applications, e.g., knowledge bases and social networks can be modeled as graphs. In such scenarios, entities are represented by the vertexes in the graphs, each of which has one class tag such as persons, attribute values and connections with other entities. With the consideration over three main components, class, relation and attribute, metalanguage for graph models is introduced to define how graph data is serialized and compiled in files or databases, e.g., eXtensible Markup Language (XML) and Resource Description Frameworks (RDFs).
Название: Cybersecurity for Smart Cities: Practices and Challenges
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Автор: Наталия Журавликова
Автор: Юрий Тарарев, Александр Тарарев
Автор: Юрий Тарарев, Александр Тарарев