Minimal probing: supporting expensive predicates for top-k queries
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Supporting top-k join queries in relational databases
The VLDB Journal — The International Journal on Very Large Data Bases
RankSQL: query algebra and optimization for relational top-k queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Semantic-Based Top-k Retrieval for Competence Management
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
R2DF framework for ranked path queries over weighted RDF graphs
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Querying the semantic web with preferences
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
On the complexity of package recommendation problems
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
On the complexity of query result diversification
Proceedings of the VLDB Endowment
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Ranking queries (or top-k queries) are dominant in many emerging applications, e.g., similarity queries in multimedia databases, searching Web databases, middleware, and data mining. The increasing importance of top-k queries warrants an efficient support of ranking in the relational database management system (RDBMS) and has recently gained the attention of the research community. 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. The following is an example top-k query.