We discuss, compare and relate some old and some new models for incomplete and probabilistic databases. We characterize the expressive power of c-tables over infinite domains and we introduce a new kind of result, algebraic completion, for studying less expressive models. By viewing probabilistic models as incompleteness models with additional probability information, we define completeness and closure under query languages of general probabilistic database models and we introduce a new such model, probabilistic c-tables, that is shown to be complete and closed under the relational algebra
The management of data uncertainty can lead to intractability, in the case of probabilistic database...
Incorporating probabilities into the semantics of incomplete databases has posed many challenges, fo...
A new model for probabilistic databases, using interval-valued conditional probability assessments, ...
We discuss, compare and relate some old and some new models for incomplete and probabilistic databas...
We discuss, compare and relate some old and some new models for incomplete and probabilistic databas...
Probabilistic databases (PDBs) model uncertainty in data in a quantitativeway. In the established fo...
In real life it is very often the case that the available knowledge is imperfect in the sense that i...
On the one hand possibility theory and possibilistic logic offer a powerful representation setting i...
Large-scale probabilistic knowledge bases are becoming increasingly important in academia and indust...
Probabilistic data and knowledge bases are becoming increasingly important in academia and industry....
Probabilistic databases are commonly known in the form of the tuple-independent model, where the val...
This article charts the tractability frontier of two classes of relational algebra queries in tuple-...
Probabilistic databases are motivated by a large and diverse set of applications that need to query ...
Probabilistic databases (PDBs) are usually incomplete, e.g., contain only the facts that have been e...
A new model for probabilistic databases, using interval-valued conditional probability assessments, ...
The management of data uncertainty can lead to intractability, in the case of probabilistic database...
Incorporating probabilities into the semantics of incomplete databases has posed many challenges, fo...
A new model for probabilistic databases, using interval-valued conditional probability assessments, ...
We discuss, compare and relate some old and some new models for incomplete and probabilistic databas...
We discuss, compare and relate some old and some new models for incomplete and probabilistic databas...
Probabilistic databases (PDBs) model uncertainty in data in a quantitativeway. In the established fo...
In real life it is very often the case that the available knowledge is imperfect in the sense that i...
On the one hand possibility theory and possibilistic logic offer a powerful representation setting i...
Large-scale probabilistic knowledge bases are becoming increasingly important in academia and indust...
Probabilistic data and knowledge bases are becoming increasingly important in academia and industry....
Probabilistic databases are commonly known in the form of the tuple-independent model, where the val...
This article charts the tractability frontier of two classes of relational algebra queries in tuple-...
Probabilistic databases are motivated by a large and diverse set of applications that need to query ...
Probabilistic databases (PDBs) are usually incomplete, e.g., contain only the facts that have been e...
A new model for probabilistic databases, using interval-valued conditional probability assessments, ...
The management of data uncertainty can lead to intractability, in the case of probabilistic database...
Incorporating probabilities into the semantics of incomplete databases has posed many challenges, fo...
A new model for probabilistic databases, using interval-valued conditional probability assessments, ...