Incomplete Information in Relational Databases
Journal of the ACM (JACM)
A probabilistic relational data model
EDBT '90 Proceedings of the 2nd international conference on extending database technology: Advances in Database Technology
Imprecise information and uncertainty in information systems
ACM Transactions on Information Systems (TOIS)
A probabilistic object-oriented data model
Data & Knowledge Engineering
A probabilistic relational model and algebra
ACM Transactions on Database Systems (TODS)
ProbView: a flexible probabilistic database system
ACM Transactions on Database Systems (TODS)
Supporting valid-time indeterminacy
ACM Transactions on Database Systems (TODS)
PSQL: a query language for probabilistic relational data
Data & Knowledge Engineering - Special issue on ER '97
A foundation of CODD's relational maybe-operations
ACM Transactions on Database Systems (TODS)
On semantic issues connected with incomplete information databases
ACM Transactions on Database Systems (TODS)
Extending the database relational model to capture more meaning
ACM Transactions on Database Systems (TODS)
The Management of Probabilistic Data
IEEE Transactions on Knowledge and Data Engineering
An Algebra for Probabilistic Databases
IEEE Transactions on Knowledge and Data Engineering
An Evidential Reasoning Approach to Attribute Value Conflict Resolution in Database Integration
IEEE Transactions on Knowledge and Data Engineering
The Theory of Probabilistic Databases
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
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Only imperfect data is available in many decision situations, which therefore plays a key role in the decision theory of economic science. It is also of key interest in computer science, among others when integrating autonomous information systems: the information in one system is often imperfect from the view of another system. The case study for the present work combines the two issues: the goal of the information integration is to provide decision support for consumers, the public. By the integration of an electronic timetable for public transport with a geographically referenced database, for example, with rental apartments, it is possible to choose alternatives, for example, rental apartments from the database that have a good transport connection to a given location. However, if the geographic references in the database are not sufficiently detailed, the quality of the public transport connections can only be characterized imprecisely. This work focuses on two issues: the representation of imprecise data and the sort operation for imprecise data. The proposed representation combines intervals and imprecise probabilities. When the imprecise data is only used for decision making with the Bernoulli-principle, a more compact representation is possible without restricting the expressive power. The key operation for decision making, the sorting of imprecise data, is discussed in detail. The new sort operation is based on so called 驴-cuts, and is particularly suitable for consumer decision support.