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Database systems have always been good at managing very large amounts of data, and they contain important functionality such as error recovery, concurrency control and security. They do, however, suffer from limited modelling capabilities, compared to the mechanisms for knowledge representation in AI systems.

An intelligent database system combines the functionality expected from a database system with much better semantic support: new data models and new functionality that lets database designers specify what the data in the database actually mean. For example, instead of just organizing data in tables as in a relational database, rules expressed in a logic-like language can be used to deduce additional data, or to extract new knowledge about their relationship. Some of this exists in commercial systems, but mostly this is a research area.

Despite what the back cover claims, the coverage both of databases and of AI is much too brief to serve as an introduction to either field. If you want an introduction to databases, get yourself a database book. After that, you can read this book, if the area is of interest to you. If you are interested in AI in general, and not the more narrow part of AI that is relevant for intelligent database systems, get an AI book.

The book is, however, essential reading for a researcher or PhD student who wants to work in the field of intelligent database systems. It is also useful and interesting for someone who has some experience with databases, and who wants both a short introduction to some advanced database topics (such as temporal databases and mediators), and a more in-depth introduction to intelligent database systems.

It may be too specific and condensed to be very useful, or easy to read, for the ACCU member who is more of a general programmer and who has less database experience.The Web& Networks