Название: Big Data and Smart Digital Environment
Автор: Yousef Farhaoui, Laila Moussaid
Издательство: Springer
Год: 2019
Страниц: 415
Язык: английский
Формат: pdf (true), epub
Размер: 74.4 MB

This book reviews the state of the art of big data analysis and smart city. It includes issues which pertain to signal processing, probability models, machine learning, data mining, database, data engineering, pattern recognition, visualisation, predictive analytics, data warehousing, data compression, computer programming, smart city, etc. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. Papers in this book were the outcome of research conducted in this field of study. The latter makes use of applications and techniques related to data analysis in general and big data and smart city in particular.

Nowadays, big data are being stored and used in various applications like Internet of Things, healthcare applications, online social networks, big science projects, and smart cities. Moreover, both structures (or definitions) of big data and their instances are evolving over time and changing at a very high speed, to reflect changes in users’ requirements or in the reference world of the database. Moreover, several modern applications, which exploit big data, require a complete history of all big data versions and all changes performed on both these data and their schemas, in order to allow (i) recovering past big data versions, (ii) tracking changes over time, and (iii) executing temporal queries on temporal big data. However, although the schema versioning technique (which consists in creating a new schema version, each time a schema change is applied, while preserving old schema versions with their corresponding data) has long been advocated to be the best solution for this issue, currently there are no available technical supports, provided by state-of-the-art big data management systems (especially NoSQL database management systems), for handling both temporal evolution and versioning aspects of big data. Therefore, the designers and developers of the aforementioned applications have to proceed in an ad hoc manner when they should deal with big data evolution while keeping track of all versions of big data and their schemas, or when they should allow time-slice queries to be evaluated, or when it is required e.g. to specify a schema for time-varying big data.

The book appeals to advanced undergraduate and graduate students, postdoctoral researchers, lecturers and industrial researchers, as well as anyone interested in big data analysis and smart city.






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