Bøker i Foundations and Trends (R) in Databases-serien

Provides a brief introduction to three distributed learning techniques that have recently been developed: lossy communication compression, asynchronous communication, and decentralized communication. These have significant impact on the work in both the system and machine learning and mathematical optimization communities.

Describes basic principles and recent developments in building approximate synopses (that is, lossy, compressed representations) of massive data. The book focuses on the four main families of synopses: random samples, histograms, wavelets, and sketches.

Surveys for a general audience the Datalog language, recursive query processing, and optimization techniques. Topics covered include the core Datalog language and various extensions, semantics, query optimizations, magic-sets optimizations, incremental view maintenance, aggregates, negation, and types.

By explaining how the result of an operation was derived from its inputs, data provenance has proven to be a useful tool that is applicable in a wide variety of applications. This monograph gives a comprehensive introduction to data provenance concepts, algorithms and methodology developed in the last few decades.

Multi-tenancy is a crucial tenet for cloud dataservice providers that allows sharing of data centre resources across tenants, thereby reducing cost. In this monograph the authors review architectures of today's cloud data services, and identify trends and challenges that arise in multi-tenant cloud data services.

Surveys fundamental concepts and practical methods for creating and curating large knowledge bases. The book covers models and methods for discovering and curating large knowledge bases from online content, with emphasis on semi-structured web pages and unstructured text sources.

Differential privacy is a promising approach to formalizing privacy - that is, for writing down what privacy means as a mathematical equation. This book serves as an overview of the state-of-the-art in techniques for differential privacy.