Optimization of Dominance Testing in Skyline Queries Using Decision Trees

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.Skyline queries identify skyline points, the minimal set of data points that dominate all other data points in a large dataset. The main challenge with skyline queries is executing the skyline query in the shortest possible time. To address and solve skyline query performance issues, we propose a decision tree-based method known as the decision tree-based comparator (DC). This method minimizes unnecessary dominance tests (i.e., pairwise comparisons) by constructing a decision tree based on the dominance testing. DC uses dominance relations that can be obtained from the decision rules of the decision tree to determine incomparability between data points. DC can also be easily applied to improve the performance of various existing skyline query methods. After describing the theoretical background of DC and applying it to existing skyline queries, we present the results of various experiments showing that DC can improve skyline query performance by up to 23.15 times.Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT)Industrial Strategic Technology Development Program funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea)