Abstract :
The result of U-Topk query simply consist of k tuples, which is not satisfactory in many cases mainly for the following two reasons: firstly, the probability of result is so small that it is hard for users to accept it, secondly, it abandons the relations between the tuples and the corresponding entities, accordingly it can´t completely reflect the real state of monitored entities. Aiming at shortage of tuple-oriented semantic of U-Topk query, this paper proposes an entity-oriented U-Topk query named as EoU-Topk as well as query processing algorithm. The basic idea of the algorithm is converting tuple-oriented probabilistic database into entity-oriented probabilistic database. In this process, some exclusive tuples that meet the pre-defined rules will be merged. The algorithm of EoU-Topk query has two advantage: firstly, it can greatly reduce the size of probabilistic database, secondly, it can truly reflect whole state of entities, and avoid the one sidedness of the tuple-oriented U-Topk query. Finally, the efficiency and quality of the EoU-Topk query proposed in the paper are verified by experiments using real data.
Keywords :
"Semantics","Bismuth","Probabilistic logic","Vehicles","Query processing","Measurement uncertainty"