Combining fuzzy information from multiple systems (extended abstract)
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient k-NN search on vertically decomposed data
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
Evaluating top-k queries over web-accessible databases
ACM Transactions on Database Systems (TODS)
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Efficient computation of the skyline cube
VLDB '05 Proceedings of the 31st international conference on Very large data bases
C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Discovering strong skyline points in high dimensional spaces
Proceedings of the 14th ACM international conference on Information and knowledge management
SUBSKY: Efficient Computation of Skylines in Subspaces
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Progressive skylining over web-accessible databases
Data & Knowledge Engineering
Refreshing the sky: the compressed skycube with efficient support for frequent updates
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
Efficient Query Processing in Arbitrary Subspaces Using Vector Approximations
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Efficient Skyline and Top-k Retrieval in Subspaces
IEEE Transactions on Knowledge and Data Engineering
Efficient processing of top-k dominating queries on multi-dimensional data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Angle-based space partitioning for efficient parallel skyline computation
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Column-stores vs. row-stores: how different are they really?
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Breaking the memory wall in MonetDB
Communications of the ACM - Surviving the data deluge
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
On Skylining with Flexible Dominance Relation
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Distance-Based Representative Skyline
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Multi-dimensional top-k dominating queries
The VLDB Journal — The International Journal on Very Large Data Bases
Understanding the meaning of a shifted sky: a general framework on extending skyline query
The VLDB Journal — The International Journal on Very Large Data Bases
Threshold-based probabilistic top-k dominating queries
The VLDB Journal — The International Journal on Very Large Data Bases
Finding maximum degrees in hidden bipartite graphs
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
International Journal of Knowledge-Based Organizations
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A top-k dominating query reports the k items with the highest domination score. Algorithms for efficient processing of this query have been recently proposed in the literature. Those methods, either index based or index free, apply a series of pruning criteria toward efficient processing. However, they are characterized by several limitations, such as (1) they lack progressiveness (they report the k best items at the end of the processing), (2) they require a multi-dimensional index or they build a grid-based index on-the-fly, which suffers from performance degradation, especially in high dimensionalities, and (3) they do not support vertically decomposed data. In this paper, we design efficient algorithms that can handle any subset of the dimensions in a progressive manner. Among the studied algorithms, the Differential Algorithm shows the best overall performance.