On the average number of maxima in a set of vectors
Information Processing Letters
Concrete mathematics: a foundation for computer science
Concrete mathematics: a foundation for computer science
The harmonic logarithms and the binomial formula
Journal of Combinatorial Theory Series A
On the Average Number of Maxima in a Set of Vectors and Applications
Journal of the ACM (JACM)
The Art of Computer Programming, 2nd Ed. (Addison-Wesley Series in Computer Science and Information
The Art of Computer Programming, 2nd Ed. (Addison-Wesley Series in Computer Science and Information
Proceedings of the 17th International Conference on Data Engineering
Robust Cardinality and Cost Estimation for Skyline Operator
ICDE '06 Proceedings of the 22nd International Conference on 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
Effective Skyline Cardinality Estimation on Data Streams
DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
Tuning the Cardinality of Skyline
Advanced Web and NetworkTechnologies, and Applications
Multi-dimensional top-k dominating queries
The VLDB Journal — The International Journal on Very Large Data Bases
Kernel-based skyline cardinality estimation
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
International Journal of Knowledge-Based Organizations
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The last years there is an increasing interest for query processing techniques that take into consideration the dominance relationship between objects to select the most promising ones, based on user preferences. Skyline and top-k dominating queries are examples of such techniques. A skyline query computes the objects that are not dominated, whereas a top-k dominating query returns the k objects with the highest domination score. To enable query optimization, it is important to estimate the expected number of skyline objects as well as the maximum domination value of an object. In this paper, we provide an estimation for the maximum domination value for data sets with statistical independence between their attributes. We provide three different methodologies for estimating and calculating the maximum domination value, and we test their performance and accuracy. Among the proposed estimation methods, our method Estimation with Roots outperforms all others and returns the most accurate results.