Finding Causality and Responsibility for Probabilistic Reverse Skyline Query Non-Answers

Causality and responsibility is an essential tool in the database community for providing intuitive explanations for answers/non-answers to queries. Causality denotes the causes for the answers/non-answers to queries, and responsibility represents the degree of a cause which reflects its influence on the answers/non-answers to queries. In this paper, we study the causality and responsibility problem (CRP) for the non-answers to probabilistic reverse skyline queries (PRSQ). We first formalize CRP on PRSQ, and then, we propose an efficient algorithm termed as CP to compute the causality and responsibility for the non-answers to PRSQ. CP first finds candidate causes, and then, it performs verification to obtain actual causes with their responsibilities, during which several strategies are used to boost efficiency. Further, we explore the CRP for the non-answers to reverse skyline queries. Towards this, we extend CP to identify directly all the actual causes and their responsibilities for a non-answer to reverse skyline queries without additional verification. Extensive experiments using both real and synthetic data sets demonstrate the effectiveness and efficiency of our presented algorithms.