Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
4-2017
Abstract
This paper explores the causality and responsibility problem (CRP) for the non-answers to probabilistic reverse skyline queries (PRSQ). Towards this, we propose an efficient algorithm called 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. Extensive experiments using both real and synthetic data sets demonstrate the effectiveness and efficiency of the presented algorithms.
Discipline
Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
Proceedings of IEEE 33rd International Conference on Data Engineering, San Diego, CA, USA, 2017 April 19-22
First Page
53
Last Page
54
Identifier
10.1109/ICDE.2017.33
City or Country
San Diego, CA, USA
Citation
GAO, Yunjun; LIU, Qing; CHEN, Gang; ZHOU, Linlin; and ZHENG, Baihua.
Finding causality and responsibility for probabilistic reverse skyline query non-answers [Extended Abstract]. (2017). Proceedings of IEEE 33rd International Conference on Data Engineering, San Diego, CA, USA, 2017 April 19-22. 53-54.
Available at: https://ink.library.smu.edu.sg/sis_research/4192
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/ICDE.2017.33