Minimal probing: supporting expensive predicates for top-k queries
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
Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Optimizing Access Cost for Top-k Queries over Web Sources: A Unified Cost-Based Approach
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
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
BATON: a balanced tree structure for peer-to-peer networks
VLDB '05 Proceedings of the 31st international conference on Very large data bases
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
Accuracy Control in Compressed Multidimensional Data Cubes for Quality of Answer-based OLAP Tools
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Processing relaxed skylines in PDMS using distributed data summaries
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
Approaching the skyline in Z order
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Best position algorithms for top-k queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Supporting personalized ranking over categorical attributes
Information Sciences: an International Journal
Search structures and algorithms for personalized ranking
Information Sciences: an International Journal
Information Sciences: an International Journal
Skyline View: Efficient Distributed Subspace Skyline Computation
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Efficient processing of multiple continuous skyline queries over a data stream
Information Sciences: an International Journal
Skyline queries on keyword-matched data
Information Sciences: an International Journal
Hi-index | 0.07 |
Skyline queries return a set of objects, or a skyline, that are not dominated by any other objects. While providing users with an intuitive query formulation, the skyline queries may incur too many results, especially, for high dimensional data. To tackle this problem, subspace skyline queries, which deals with a subset of dimensions, have been recently studied. To identify interesting skylines, users can iteratively refine multiple relevant subspaces for skyline queries. Existing work focuses primarily on supporting efficient subspace skyline computation in centralized databases. In clear contrast, this paper aims to address subspace skyline computation in distributed environments such as the Web. Toward this goal, we make use of pre-computed subspace skylines as views in databases, called skyline views. Specifically, we propose distributed subspace skyline computation which minimizes the total access cost by leveraging the skyline views. Our experimental results validate that our proposed algorithms significantly outperform state-of-the-art algorithms in extensive synthetic datasets.