A novel dynamic skyline operation for multicriteria decision support

The skyline operation is a typical Multicriteria Decision Making (MCDM) that has been well studied in database context. The basic assumption of conventional skyline operator is preference-ordered values within multi-dimensional decision tables. This assumption utilizes preference-ordered values to simplify the complex human preference, which is subject to big challenges in real applications. In this paper, we firstly investigate preference relations on skyline operation and lead to a dynamic preference model. We then introduce the concept of preference intensity and propose a new decision model, called Tolerant Skyline Operation (T-skyline). We study the method for computation of T-skyline and address the issue of continuous T-skyline maintenance. Through a detailed case study related to the NBA player evaluation in 2010-11 regular seasons, we demonstrate the effectiveness and advantages of the proposed decision model.