A survey on rank aware query processing techniques

Ranking is an important property that needs to be fully supported by current relational query engines. Given a set of objects for all functions F over P, an interesting problem is to compute the top ranked objects for all functions. Ranking queries (or top-k queries) are dominant in many emerging applications, e.g., similarity queries in multimedia databases, searching Web databases, and data mining. Top-k queries aim at providing only the top k query results, according to a user-specified ranking function, which in many cases is an aggregate of multiple criteria. In this survey we describe top-k processing techniques and show the implications of each dimension on the design of the underlying techniques.