Books in the Foundations and Trends (R) in Databases series

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.

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.