Incompleteness due to missing attribute values (aka “null values”) is very common in autonomous web databases, on which user accesses are usually.

Empirical studies demonstrate the effectiveness of our approach in retrieving relevant uncertain answers with high precision, high recall and manageable cost.

Incompleteness due to missing attribute values (aka “null values”) is very common in autonomous web databases, on which user accesses are usually supported ...

This thesis presents QPIAD – a framework for query processing over incomplete autonomous databases. ... Query Processing over Incomplete Autonomous Databases . .

What is hard? – Retrieving relevant uncertain tuples with missing values. – Rewriting queries given the limited query access patterns ...

We introduce a novel query rewriting and optimization framework QPIAD that tackles these challenges. Our technique involves reformulating the user query based ...

We introduce a novel query rewriting and optimization framework QPIAD that tackles these challenges to retrieve relevant uncertain answers. Our technique ...

Our technique involves reformulating the user query based on approximate func-tional dependencies (AFDs) among the database attributes. The reformulated queries ...

This work introduces a novel query rewriting and optimization framework QPIAD, which involves reformulating the user query based on mined correlations among ...

We introduce a novel query rewriting and optimization framework QPIAD that tackles these challenges. Our technique involves reformulating the user query based ...