Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 145-161).

Preface: a great promise -- Acknowledgments --

1. Overview -- Two examples -- Key concepts -- Probabilities and their meaning in databases -- Possible worlds semantics -- Types of uncertainty -- Types of probabilistic databases -- Query semantics -- Lineage -- Probabilistic databases v.s. graphical models -- Safe queries, safe query plans, and the dichotomy -- Applications of probabilistic databases -- Bibliographic and historical notes --

2. Data and query model -- Background of the relational data model -- The probabilistic data model -- Query semantics -- Views: possible answer sets semantics -- Queries: possible answers semantics -- C-tables and PC-tables -- Lineage -- Properties of a representation system -- Simple probabilistic database design -- Tuple-independent databases -- BID databases -- U-databases -- Bibliographic and historical notes --

3. The query evaluation problem -- The complexity of P([phi]) -- The complexity of P(Q) -- Bibliographic and historical notes --

4. Extensional query evaluation -- Query evaluation using rules -- Query independence -- Six simple rules for P(Q) -- Examples of unsafe (intractable) queries -- Examples of safe (tractable) queries -- The möbius function -- Completeness -- Query evaluation using extensional plans -- Extensional operators -- An algorithm for safe plans -- Extensional plans for unsafe queries -- Extensions -- BID tables -- Deterministic tables -- Keys in the representation -- Bibliographic and historical notes --

5. Intensional query evaluation -- Probability computation using rules -- Five simple rules for P([phi]) -- An algorithm for P([phi]) -- Read-once formulas -- Compiling P([phi]) -- d-DNNF -- FBDD -- OBDD -- Read-once formulas -- Approximating P([phi]) -- A deterministic approximation algorithm -- Monte Carlo approximation -- Query compilation -- Conjunctive queries without self-joins -- Unions of conjunctive queries -- Discussion -- Bibliographic and historical notes --

6. Advanced techniques -- Top-k query answering -- Computing the set top-k -- Ranking the set top-k -- Sequential probabilistic databases -- Monte Carlo databases -- The MCDB data model -- Query evaluation in MCDB -- Indexes and materialized views -- Indexes for probabilistic data -- Materialized views for relational probabilistic databases --

Conclusion -- Bibliography -- Authors' biographies.

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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 many 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.

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