关键词: 海量不完整数据, 维度组合, Skyline

Abstract: With the rapid development of Internet, Internet of things and other information technology, and multi-dimensional data increasing, these massive data are often accompanied by a large number of incomplete data. So how to efficiently get the approximate result sets required by users from the massive incomplete data is an urgent problem to solve. This paper proposes a Skyline query algorithm for the massive high-dimensional incomplete data sets based on combination of dimensions. The algorithm constitutes RankList data structure to improve query efficiency and reduce the impact of incomplete data for query results, divides query subspaces by combining different dimensions, and incrementally checks out the highest priority point in the subspace, that is Skyline points uniformly distributed in the incomplete data set. The experimental results show that, compared with the Iskyline algorithm, the query efficiency of the proposed algorithm increases by 85% on average. And when the data are huge amount and high dimension, the algorithm shows higher query efficiency than the ordinary methods.

Key words: massive incomplete data, combinational dimensions, Skyline