Skyline Computation and Maintenance over Imperfect Databases: A Marginal-Points-Based Approach
Sayda Elmi, Allel Hadjali, Mohamed Anis Bach Tobji, Boutheina Ben Yaghlane · 2017
In the last decade, skyline queries have attracted the interest of several researchers in the database field due to their ability to retrieve interesting objects among a large set of objects. Skyline analysis is a powerful tool in a wide spectrum of real applications including multi-criteria optimal decision making, preference answering and many applications where uncertain, imprecise and noisy data inherently exist. As large amounts of distributed data over Internet are communicated and shared, an important problem is to retrieve the global skyline from all the distributed local sites. In addition, though the skyline queries can control selection, there exist not much works that can handle skyline queries under database updates. In this paper, based on the marginal points notions, we introduce new methods to efficiently compute the global skyline from distributed local sites and over frequently updated databases. The efficiency and effectiveness of our proposal are verified by extensive experimental results.