The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Combining fuzzy information from multiple systems (extended abstract)
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)
The onion technique: indexing for linear optimization queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A cost model for query processing in high dimensional data spaces
ACM Transactions on Database Systems (TODS)
Proceedings of the 17th International Conference on Data Engineering
X-means: Extending K-means with Efficient Estimation of the Number of Clusters
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Algorithms and applications for answering ranked queries using ranked views
The VLDB Journal — The International Journal on Very Large Data Bases
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
KLEE: a framework for distributed top-k query algorithms
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
Skyline Queries Against Mobile Lightweight Devices in MANETs
ICDE '06 Proceedings of the 22nd International Conference on Data 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
Branch-and-bound processing of ranked queries
Information Systems
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
On domination game analysis for microeconomic data mining
ACM Transactions on Knowledge Discovery from Data (TKDD)
Tuning the Cardinality of Skyline
Advanced Web and NetworkTechnologies, and Applications
Reaching the Top of the Skyline: An Efficient Indexed Algorithm for Top-k Skyline Queries
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Efficient mining of skyline objects in subspaces over data streams
Knowledge and Information Systems
Aggregate computation over data streams
APWeb'08 Proceedings of the 10th Asia-Pacific web conference on Progress in WWW research and development
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
Supporting ranking queries on uncertain and incomplete data
The VLDB Journal — The International Journal on Very Large Data Bases
A clustering based approach for skyline diversity
Expert Systems with Applications: An International Journal
Parallel skyline computation on multicore architectures
Information Systems
Efficient and generic evaluation of ranked queries
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Efficient evaluation of location-dependent skyline queries using non-dominance scopes
Proceedings of the 2nd International Conference on Computing for Geospatial Research & Applications
SkyMap: a trie-based index structure for high-performance skyline query processing
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Progressive processing of subspace dominating queries
The VLDB Journal — The International Journal on Very Large Data Bases
Processing generalized k-nearest neighbor queries on a wireless broadcast stream
Information Sciences: an International Journal
Subspace top-k query processing using the hybrid-layer index with a tight bound
Data & Knowledge Engineering
Computing immutable regions for subspace top-k queries
Proceedings of the VLDB Endowment
Monochromatic and bichromatic mutual skyline queries
Expert Systems with Applications: An International Journal
Efficient entity matching using materialized lists
Information Sciences: an International Journal
Toward efficient multidimensional subspace skyline computation
The VLDB Journal — The International Journal on Very Large Data Bases
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Skyline and top-k queries are two popular operations for preference retrieval. In practice, applications that require these operations usually provide numerous candidate attributes, whereas, depending on their interests, users may issue queries regarding different subsets of the dimensions. The existing algorithms are inadequate for subspace skyline/top-k search because they have at least one of the following defects: 1) They require scanning the entire database at least once, 2) they are optimized for one subspace but incur significant overhead for other subspaces, or 3) they demand expensive maintenance cost or space consumption. In this paper, we propose a technique SUBSKY, which settles both types of queries by using purely relational technologies. The core of SUBSKY is a transformation that converts multidimensional data to one-dimensional (1D) values. These values are indexed by a simple B-tree, which allows us to answer subspace queries by accessing a fraction of the database. SUBSKY entails low maintenance overhead, which equals the cost of updating a traditional B-tree. Extensive experiments with real data confirm that our technique outperforms alternative solutions significantly in both efficiency and scalability.