The skyline query is a most useful tool to find out attractive products. However, it does little to help select the product combinations with the maximum discount rate. Motivated by this, we identify an interesting problem, a most preferential skyline product (MPSP) combination discovering problem, which is NP-hard, for the first time in the literature. This problem aims to report all skyline product combinations having the maximum discount rate. Since the exact algorithm for the MPSP is not scalable to large or high-dimensional datasets, we design an incremental greedy algorithm. The experiment results demonstrate the efficiency and effectiveness of the proposed algorithm.
['Zhibang Yang', 'Xu Zhou', 'Yifu Zeng', 'Fei Zeng', 'Yantao Zhou']
Identifying most preferential skyline product combinations under price promotion