A new book entitled 'Probabilistic Databases' has been recently published by Dan Olteanu in collaboration with Christoph Koch from EPFL, Christopher Re from the University of Wisconsin-Madison, and Dan
Suciu from the University of Washington.

Probabilistic databases are databases where the value of some attributes, or the presence of some records are uncertain, and known only with some probability.  Applications in areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of uncertain data, which are best modeled and processed by a probabilistic database.

This book presents a first unified view of the state of the art in representation formalisms and query processing techniques for probabilistic data. It also surveys advanced work on compilation of queries into decision diagrams, sequential probabilistic databases, indexes, and Monte Carlo databases.

The book is intended for researchers, either in databases or probabilistic inference, or as a textbook for an advanced graduate class.

Dan Olteanu has been a faculty in the Department of Computer Science at the University of Oxford since September 2007.

Probabilistic Databases. Dan Suciu, Dan Olteanu, Christopher Re, and Christoph Koch. 180 pages. 2011.  ISBN: paper 9781608456802, ebook 9781608456819.

Book's web page: http://dx.doi.org/10.2200/S00362ED1V01Y201105DTM016