Exploiting Lineage for Confidence Computation in Uncertain and Probabilistic Databases

Das Sarma, Anish and Theobald, Martin and Widom, Jennifer (2008) Exploiting Lineage for Confidence Computation in Uncertain and Probabilistic Databases. In: 24th International Conference on Data Engineering (ICDE 2008).

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We study the problem of computing query results with confidence values in ULDBs: relational databases with uncertainty and lineage. ULDBs, which subsume probabilistic databases, offer an alternative decoupled method of computing confidence values: Instead of computing confidences during query processing, compute them afterwards based on lineage. This approach enables a wider space of query plans, and it permits selective computations when not all confidence values are needed. This paper develops a suite of algorithms and optimizations for a broad class of relational queries on ULDBs. We provide confidence computation algorithms for single data items, as well as efficient batch algorithms to compute confidences for an entire relation or database. All algorithms incorporate memoization to avoid redundant computations, and they have been implemented in the Trio prototype ULDB database system. Performance characteristics and scalability of the algorithms are demonstrated through experimental results over a large synthetic dataset.

Item Type: Conference or Workshop Item (Paper)
Subjects: DBIS Research > Publications
Divisions: Faculty of Engineering, Electronics and Computer Science > Institute of Databases and Informations Systems > DBIS Research and Teaching > DBIS Research > Publications
Depositing User: Prof. Dr. Martin Theobald
Date Deposited: 09 Sep 2015 19:46
Last Modified: 09 Sep 2015 19:46
URI: http://dbis.eprints.uni-ulm.de/id/eprint/1249

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