Representative Skyline Queries With Total and Partial Order Domains Using US-ELM

Representative Skyline Queries With Total and Partial Order Domains Using US-ELM

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Skyline queries play an important role in multiple criteria decision making problems.A representative skyline set contains k skyline points that can represent its full skyline set, which is more significant.The distance-based representative skyline (k-DRS) is a kind of representative skyline, which can describe the tradeoffs among different dimensions offered by the full skyline set.The Shopping Totes previous works only focus on the k-DRS queries in total order domains.In this paper, we focus on the k-DRS problem in both total and partial order (PO) domains.

Since k-DRS is a NP-hard problem in d-dimensional (d ≥ 3) space, it is impossible to calculate the exact k-DRS in d-dimensional space.By in-depth analyzing the properties of the k-DRS, we propose an algorithm k-DRS query algorithm in total and partial order (DRSTP) to solve the k-DRS problem from a new perspective.In DRSTP, first, a value in PO domain is transformed to numerical values in total order domains.Thus, the distance of any two partial values can be measured using the transformed values.Then, we apply US-ELM to divide the full skyline set into k clusters.

Next, in each cluster, we design a method to select a point as the representative point.Experimental results show that our DRSTP significantly outperforms its competitors in terms of both accuracy COQ10 300MG and efficiency.