A model for the prediction of R-tree performance
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
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
Progressive approximate aggregate queries with a multi-resolution tree structure
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
STR: A Simple and Efficient Algorithm for R-Tree Packing
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
Efficient OLAP Operations in Spatial Data Warehouses
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Stabbing the Sky: Efficient Skyline Computation over Sliding Windows
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Stratified computation of skylines with partially-ordered domains
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Maximal vector computation in large data sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Efficient computation of the skyline cube
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Catching the best views of skyline: a semantic approach based on decisive subspaces
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Robust Cardinality and Cost Estimation for Skyline Operator
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
SUBSKY: Efficient Computation of Skylines in Subspaces
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Skyline Queries Against Mobile Lightweight Devices in MANETs
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Supporting ad-hoc ranking aggregates
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Finding k-dominant skylines in high dimensional space
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
DADA: a data cube for dominant relationship analysis
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Alternative Algorithm for Hilbert's Space-Filling Curve
IEEE Transactions on Computers
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Probabilistic ranked queries in uncertain databases
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Pruning attribute values from data cubes with diamond dicing
IDEAS '08 Proceedings of the 2008 international symposium on Database engineering & applications
Tuning the Cardinality of Skyline
Advanced Web and NetworkTechnologies, and Applications
Top-k dominating queries in uncertain databases
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Top-k dominant web services under multi-criteria matching
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Multi-dimensional top-k dominating queries
The VLDB Journal — The International Journal on Very Large Data Bases
Scalable skyline computation using object-based space partitioning
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Toward context and preference-aware location-based services
Proceedings of the Eighth ACM International Workshop on Data Engineering for Wireless and Mobile Access
Continuous Processing of Preference Queries in Data Streams
SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
Processing top-N relational queries by learning
Journal of Intelligent Information Systems
Threshold-based probabilistic top-k dominating queries
The VLDB Journal — The International Journal on Very Large Data Bases
A demonstration of FlexPref: extensible preference evaluation inside the DBMS engine
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Z-SKY: an efficient skyline query processing framework based on Z-order
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient processing of exact top-k queries over disk-resident sorted lists
The VLDB Journal — The International Journal on Very Large Data Bases
Data & Knowledge Engineering
Identifying the most influential user preference from an assorted collection
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
Continuous skyline monitoring over distributed data streams
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
Estimation of the maximum domination value in multi-dimensional data sets
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
CareDB: a context and preference-aware location-based database system
Proceedings of the VLDB Endowment
Ranking uncertain sky: The probabilistic top-k skyline operator
Information Systems
Progressive processing of subspace dominating queries
The VLDB Journal — The International Journal on Very Large Data Bases
Transitivity-preserving skylines for partially ordered domains
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
Time-HOBI: Index for optimizing star queries
Information Systems
On optimality-ratio and coverage in ranking of joined search results
Distributed and Parallel Databases
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Probabilistic top-k dominating queries in uncertain databases
Information Sciences: an International Journal
SkyDiver: a framework for skyline diversification
Proceedings of the 16th International Conference on Extending Database Technology
Flexible and extensible preference evaluation in database systems
ACM Transactions on Database Systems (TODS)
GeoRank: an efficient location-aware news feed ranking system
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Monochromatic and bichromatic mutual skyline queries
Expert Systems with Applications: An International Journal
Probabilistic top-K dominating services composition with uncertain QoS
Service Oriented Computing and Applications
International Journal of Knowledge-Based Organizations
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The top-k dominating query returns k data objects which dominate the highest number of objects in a dataset. This query is an important tool for decision support since it provides data analysts an intuitive way for finding significant objects. In addition, it combines the advantages of top-k and skyline queries without sharing their disadvantages: (i) the output size can be controlled, (ii) no ranking functions need to be specified by users, and (iii) the result is independent of the scales at different dimensions. Despite their importance, top-k dominating queries have not received adequate attention from the research community. In this paper, we design specialized algorithms that apply on indexed multi-dimensional data and fully exploit the characteristics of the problem. Experiments on synthetic datasets demonstrate that our algorithms significantly outperform a previous skyline-based approach, while our results on real datasets show the meaningfulness of top-k dominating queries.