Top-k Dominating Queries on Skyline Groups

Abstract

The top-k dominating (TKD) query on skyline groups returns k skyline groups that dominate the maximum number of points in a given data set. The TKD query combines the advantages of skyline groups and top-k dominating queries, thus has been frequently used in decision making, recommendation systems, and quantitative economics. Traditional skylines are inadequate to answer queries from both individual and groups of points. The group size could be too large to be processed in a reasonable time as a single operator (i.e., the skyline group operator). In this paper, we address the performance problem of grouping for TKD queries in skyline database. We formulate the problem of grouping, define the group operator in skyline, and propose several efficient algorithms to find top-k skyline groups. Thus, we provide a systematic study of TKD queries on skyline groups and validate our algorithms with extensive empirical results on synthetic and realworld data.