Skyline sets queries from databases with missing values

With the increase of data volume, advanced query operators, such as skyline queries, are necessary in order to help users to handle the huge amount of available data by identifying a set of interesting data objects. Skyline queries help us to filter unnecessary information efficiently and provide us clues for various decision making tasks. Most of the existing skyline algorithms can not preserve individual´s privacy and are not well suited for data with outliers and frequently updated data. Considering these issues, earlier we have proposed skyline sets queries from databases where all dimensions are available for all data items. Let s be the number of objects in each set and n be the number of objects in the database. The number of sets in the database is _nC_s. Skyline sets query returns all skyline s-sets from _nC_s sets. We consider an efficient algorithm for computing “convex” skyline of the _nC_s sets. In this paper, we use the idea for skyline sets queries from databases with missing values and propose a method, namely, RBSSQ. RBSSQ method uses a replacement based approach and is applicable to the databases having any number of missing dimensions in the database objects. We have conducted several experiments in terms of computational cost and found that our proposed method can efficiently compute skyline sets from data items with missing values.