Publication Type

Journal Article

Version

acceptedVersion

Publication Date

11-2016

Abstract

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.

Keywords

Probabilistic logic, Algorithm design and analysis, Object recognition, Database systems, Relational databases, Decision making

Discipline

Numerical Analysis and Scientific Computing | Theory and Algorithms

Research Areas

Data Science and Engineering

Publication

IEEE Transactions on Knowledge and Data Engineering

Volume

28

Issue

11

First Page

2974

Last Page

2987

ISSN

1041-4347

Identifier

10.1109/TKDE.2016.2599869

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/TKDE.2016.2599869

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