Combining fuzzy information from multiple systems (extended abstract)
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Fuzzy queries in multimedia database systems
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
The onion technique: indexing for linear optimization queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Approximating multi-dimensional aggregate range queries over real attributes
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
PREFER: a system for the efficient execution of multi-parametric ranked queries
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Minimal probing: supporting expensive predicates for top-k queries
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Top-k selection queries over relational databases: Mapping strategies and performance evaluation
ACM Transactions on Database Systems (TODS)
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Incorporating User Preferences in Multimedia Queries
ICDT '97 Proceedings of the 6th International Conference on Database Theory
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Evaluating Top-k Selection Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Probabilistic Optimization of Top N Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Optimizing Multi-Feature Queries for Image Databases
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Supporting Incremental Join Queries on Ranked Inputs
Proceedings of the 27th International Conference on Very Large Data Bases
Selectivity Estimation Without the Attribute Value Independence Assumption
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Evaluating Top-k Queries over Web-Accessible Databases
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Evaluating top-k queries over web-accessible databases
ACM Transactions on Database Systems (TODS)
Supporting top-k join queries in relational databases
The VLDB Journal — The International Journal on Very Large Data Bases
Top-k query evaluation with probabilistic guarantees
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Probabilistic ranked queries in uncertain databases
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Ad-hoc aggregations of ranked lists in the presence of hierarchies
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
ER '08 Proceedings of the 27th International Conference on Conceptual Modeling
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Robust and efficient algorithms for rank join evaluation
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
SAIL: Structure-aware indexing for effective and progressive top-k keyword search over XML documents
Information Sciences: an International Journal
Harnessing the strengths of anytime algorithms for constant data streams
Data Mining and Knowledge Discovery
Efficient wikipedia-based semantic interpreter by exploiting top-k processing
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Top-k vectorial aggregation queries in a distributed environment
Journal of Parallel and Distributed Computing
R2DF framework for ranked path queries over weighted RDF graphs
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Precise anytime clustering of noisy sensor data with logarithmic complexity
Proceedings of the Fifth International Workshop on Knowledge Discovery from Sensor Data
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Proceedings of the 15th International Conference on Extending Database Technology
A context-aware scheme for privacy-preserving location-based services
Computer Networks: The International Journal of Computer and Telecommunications Networking
Provisional reporting for rank joins
Journal of Intelligent Information Systems
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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Top-k queries on large multi-attribute data sets are fundamental operations in information retrieval and ranking applications. In this paper, we initiate research on the anytime behavior of top-k algorithms. In particular, given specific top-k algorithms (TA and TA-Sorted) we are interested in studying their progress toward identification of the correct result at any point during the algorithms' execution. We adopt a probabilistic approach where we seek to report at any point of operation of the algorithm the confidence that the top-k result has been identified. Such a functionality can be a valuable asset when one is interested in reducing the runtime cost of top-k computations. We present a thorough experimental evaluation to validate our techniques using both synthetic and real data sets.