Efficient Analyzing General Dominant Relationship Based On Partial Order Models

Skyline query is very important because it is the basis of many applications, e.g., decision making, user-preference queries. Given an N-dimensional dataset D. a point p is said to dominate another point q if p is better than q in at least one dimension and equal to or better than q in the remaining dimensions. In this paper, we study a generalized problem of skyline query that, users are more interested in the details of the dominant relationship in a dataset, i.e., a point p dominates how many other points and whom they are. We show that the existing framework proposed in [17] can not efficiently solve this problem. We find the interrelated connection between the partial order and the dominant relationship. Based on this discovery, we propose a new data structure, Par Cube, which concisely represents the dominant relationship. We propose some effective strategies to construct Par Cube. Extensive experiments illustrate the efficiency of our methods.