Probabilistic ranking over relations
Proceedings of the 13th International Conference on Extending Database Technology
Efficient processing of exact top-k queries over disk-resident sorted lists
The VLDB Journal — The International Journal on Very Large Data Bases
Ranking under temporal constraints
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
An access cost-aware approach for object retrieval over multiple sources
Proceedings of the VLDB Endowment
Learning to rank under tight budget constraints
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Efficient early top-k query processing in overloaded P2P systems
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
High-performance processing of text queries with tunable pruned term and term pair indexes
ACM Transactions on Information Systems (TOIS)
Evaluating top-k algorithms with various sources of data and user preferences
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
Bulk sorted access for efficient top-k retrieval
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
As-Soon-As-Possible top-k query processing in p2p systems
Transactions on Large-Scale Data- and Knowledge-centered systems IX
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We consider a novel problem of top-k query processing under budget constraints. We provide both a framework and a set of algorithms to address this problem. Existing algorithms for top-k processing are budget-oblivious, i.e., they do not take budget constraints into account when making scheduling decisions, but focus on the performance to compute the final top-k results. Under budget constraints, these algorithms therefore often return results that are a lot worse than the results that can be achieved with a clever, budget-aware scheduling algorithm. This paper introduces novel algorithms for budget-aware top-k processing that produce results that have a significantly higher quality than those of state-of-the-art budget-oblivious solutions.