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Conditioning Probabilistic Relational Data with Referential Constraints

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dc.contributor.author TANG, Ruiming en_US
dc.contributor.author SHAO, Dongxu en_US
dc.contributor.author BA, M. Lamine en_US
dc.contributor.author WU, Huayu en_US
dc.date.accessioned 2014-03-12T08:46:48Z en_US
dc.date.accessioned 2017-01-23T07:00:08Z
dc.date.available 2014-03-12T08:46:48Z en_US
dc.date.available 2017-01-23T07:00:08Z
dc.date.issued 2014-03-12T08:46:48Z en_US
dc.identifier.uri http://hdl.handle.net/1900.100/4361 en_US
dc.description.abstract A probabilistic relational database is a compact form of a set of deterministic relational databases (namely, possible worlds), each of which has a probability. In our framework, the existence of tuples is determined by associated Boolean formulae based on elementary events. An estimation, within such a setting, of the probabilities of possible worlds uses a prior probability distribution speci ed over the elementary events. Direct observations and general knowledge, in the form of constraints, help re ning these probabilities, possibly ruling out some possible worlds. More precisely, new constraints can translate the observation of the existence or non-existence of a tuple, the knowledge of a well-de ned rule, such as primary key constraint, foreign key constraint, referential constraint, etc. Informally, the process of enforcing knowledge on a probabilistic database, which consists of computing a new subset of valid possible worlds together with their new (conditional) probabilities, is called conditioning. In this paper, we are interested in nding a new probabilistic relational database after conditioning with referential constraints involved. In the most general case, conditioning is intractable. As a result, we restricted our study to probabilistic relational databases in which formulae of tuples are independent events in order to achieve some tractability results. We devise and present polynomial algorithms for conditioning probabilistic relational databases with referential constraints. en_US
dc.format.extent 426853 bytes en_US
dc.format.mimetype application/pdf en_US
dc.language.iso en en_US
dc.relation.ispartofseries ;TRB3/2014 en_US
dc.title Conditioning Probabilistic Relational Data with Referential Constraints en_US
dc.type Technical Report en_US

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