D-SKY: A Framework for Processing Skyline Queries in a Dynamic and Incomplete Database

摘要: Processing skyline queries in incomplete data is challenging, particularly, for a database with dynamic contents which the frequently updated. These update operations not only affect computation, but also influence results. Furthermore, incompleteness of raises issue losing transitivity property technique, leads to problem cyclic dominance. It undesirable process on and by directly applying over entire updated due prohibitive cost. Thus, this paper proposes framework called D-SKY processing database. aims at avoiding scanning whole after an operation performed identify new skylines. In paper, we consider case insert operation, adding items. exploits existing skylines newly added dominated items before process. Therefore, large amount pruned, reduces number domination tests be conducted helps performed. Experiment result both real synthetic datasets demonstrates that our solution outperforms solutions terms reducing pairwise comparisons time.