International audienceThe term naive evaluation refers to evaluating queries over incomplete databases as if nulls were usual data values, i.e., to using the standard database query evaluation engine. Since the semantics of query answering over incomplete databases is that of certain answers, we would like to know when naive evaluation computes them: i.e., when certain answers can be found without inventing new specialized algorithms. For relational databases it is well known that unions of conjunctive queries possess this desirable property, and results on preservation of formulae under homomorphisms tell us that within relational calculus, this class cannot be extended under the open-world assumption. Our goal here is twofold. First, we d...
Data completeness is commonly regarded as one of the key aspects of data quality. With this paper we...
One of the most common scenarios of handling incomplete information occurs in relational databases. ...
To combine and query ordered data from multiple sources, one needs to handle uncertainty about the p...
International audienceThe term naive evaluation refers to evaluating queries over incomplete databas...
International audienceThe term naïve evaluation refers to evaluating queries over incomplete databas...
The term näıve evaluation refers to evaluating queries over incomplete databases as if nulls were u...
The term näıve evaluation refers to evaluating queries over incomplete databases as if nulls were u...
Handling incomplete data in a correct manner is a notoriously hard problem in databases. Theoretical...
AbstractWe study here the complexity of evaluating quaries in logical databases. We focus on Reither...
To answer database queries over incomplete data the gold standard is finding certain answers: those ...
Querying incomplete data is an important task both in data management, and in many AI applications t...
AbstractSemistructured data occur in situations where information lacks a homogeneous structure and ...
AbstractIn databases, queries are usually defined on complete databases. In this paper we introduce ...
International audienceBuilding reliable systems over partially complete data poses significant chall...
While all relational database systems are based on the bag data model, much of theoretical research ...
Data completeness is commonly regarded as one of the key aspects of data quality. With this paper we...
One of the most common scenarios of handling incomplete information occurs in relational databases. ...
To combine and query ordered data from multiple sources, one needs to handle uncertainty about the p...
International audienceThe term naive evaluation refers to evaluating queries over incomplete databas...
International audienceThe term naïve evaluation refers to evaluating queries over incomplete databas...
The term näıve evaluation refers to evaluating queries over incomplete databases as if nulls were u...
The term näıve evaluation refers to evaluating queries over incomplete databases as if nulls were u...
Handling incomplete data in a correct manner is a notoriously hard problem in databases. Theoretical...
AbstractWe study here the complexity of evaluating quaries in logical databases. We focus on Reither...
To answer database queries over incomplete data the gold standard is finding certain answers: those ...
Querying incomplete data is an important task both in data management, and in many AI applications t...
AbstractSemistructured data occur in situations where information lacks a homogeneous structure and ...
AbstractIn databases, queries are usually defined on complete databases. In this paper we introduce ...
International audienceBuilding reliable systems over partially complete data poses significant chall...
While all relational database systems are based on the bag data model, much of theoretical research ...
Data completeness is commonly regarded as one of the key aspects of data quality. With this paper we...
One of the most common scenarios of handling incomplete information occurs in relational databases. ...
To combine and query ordered data from multiple sources, one needs to handle uncertainty about the p...