Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
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
Finding k-dominant skylines in high dimensional space
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
SaLSa: computing the skyline without scanning the whole sky
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Probabilistic skylines on uncertain data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficient computation of reverse skyline queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Skyline Query Processing for Incomplete Data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
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
A survey of skyline processing in highly distributed environments
The VLDB Journal — The International Journal on Very Large Data Bases
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In the last decade, skyline queries have been extensively studied for different domains because of their wide applications in multi-criteria decision making and search space pruning. A skyline query returns all the interesting points in a multi-dimensional data set that are not dominated by any other point with respect to all dimensions. However, real world data sets are seldom complete, i.e. data points often have missing values in one or more dimensions. Traditional skyline query processing algorithms developed for complete data can not be easily adapted for such situations because of the non-transitive and potentially cyclic nature of dominance relation that arises in the case of incomplete data. Unfortunately, skyline query processing for such incomplete data has not received enough attention. We propose an efficient Sort-based Incomplete Data Skyline (SIDS) algorithm to compute the skyline points over incomplete data. Extensive experiments on both real world and synthetic data sets demonstrate the efficiency and scalability of our approach over current state of the art approach.