Abstract
The reverse skyline query is a useful tool for multi-criteria decision making. However, users may be frustrated by having a cardinality-based unexpected query result such as too few answers (including empty answer) or too many answers. In this chapter, we aim at exploring why-few and why-many questions on reverse skyline queries in order to help users arrive at the query with the expected query result cardinality. Given an initial reverse skyline query whose query result is too few (even empty) or too many and a desired cardinality constraint for the query result, answering why-few and why-many questions on reverse skyline queries should provide suggestions on how to refine the initial query with the minimum penalty such that the refined query result satisfies the specified cardinality constraint. To efficiently answer why-few and why-many questions on reverse skyline queries, we propose two approaches which utilize the techniques of pre-computation, space partitioning, and pruning strategies to boost performance. Extensive experimental evaluation demonstrates the effectiveness and efficiency of the presented algorithms.
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Gao, Y., Liu, Q. (2017). Why-Few and Why-Many Questions on Reverse Skyline Queries. In: Preference Query Analysis and Optimization. SpringerBriefs in Computer Science. Springer, Singapore. https://doi.org/10.1007/978-981-10-6635-1_4
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DOI: https://doi.org/10.1007/978-981-10-6635-1_4
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