Efficient Skyline Computation on Massive Incomplete Data

Abstract Incomplete skyline query is an important operation to filter out pareto-optimal tuples on incomplete data. It harder than due intransitivity and cyclic dominance. analyzed that the existing algorithms cannot process massive data efficiently. This paper proposes a novel table-scan-based TSI algorithm deal with high efficiency. solves issues of dominance by two separate stages. In stage 1, computes candidates sequential scan table. The dominated others are discarded directly in 1. 2, refines another scan. pruning devised this reduce execution cost TSI. By assistant structures, can skip majority phase 1 without retrieving it actually. extensive experimental results, which conducted synthetic real-life sets, show compute