Combining fuzzy information from multiple systems (extended abstract)
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
ProbView: a flexible probabilistic database system
ACM Transactions on Database Systems (TODS)
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)
The Management of Probabilistic Data
IEEE Transactions on Knowledge and Data Engineering
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
Query Processing Issues in Image(Multimedia) Databases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
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)
Querying Imprecise Data in Moving Object Environments
IEEE Transactions on Knowledge and Data Engineering
Supporting top-k join queries in relational databases
The VLDB Journal — The International Journal on Very Large Data Bases
Indexing multi-dimensional uncertain data with arbitrary probability density functions
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Top-k query evaluation with probabilistic guarantees
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficient indexing methods for probabilistic threshold queries over uncertain data
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
Efficient Processing of Top-k Queries in Uncertain Databases with x-Relations
IEEE Transactions on Knowledge and Data Engineering
Efficiently Answering Probabilistic Threshold Top-k Queries on Uncertain Data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Efficient processing of exact top-k queries over disk-resident sorted lists
The VLDB Journal — The International Journal on Very Large Data Bases
Providing built-in keyword search capabilities in RDBMS
The VLDB Journal — The International Journal on Very Large Data Bases
Bulk loading hierarchical mixture models for efficient stream classification
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
BT*: an advanced algorithm for anytime classification
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Provisional reporting for rank joins
Journal of Intelligent Information Systems
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
A probabilistic optimization framework for the empty-answer problem
Proceedings of the VLDB Endowment
Hi-index | 0.00 |
Top-k queries on large multi-attribute data sets are fundamental operations in information retrieval and ranking applications. In this article, we initiate research on the anytime behavior of top-k algorithms on exact and fuzzy data. 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.