This paper proposes a ranking method to exploit statistical correlations among pairs of attribute values in relational databases. For a given query, the correlations of the query ...
Probabilistic top-k ranking queries have been extensively studied due to the fact that data obtained can be uncertain in many real applications. A probabilistic top-k ranking quer...
There has been a great deal of interest in recent years on ranking query results in relational databases. This paper presents a novel method to rank objects (e.g., tuples) by explo...
Abstract-- When dealing with massive quantities of data, topk queries are a powerful technique for returning only the k most relevant tuples for inspection, based on a scoring func...
We investigate the problem of ranking answers to a database query when many tuples are returned. We adapt and apply principles of probabilistic models from Information Retrieval f...