The VLDB Journal

, Volume 25, Issue 6, pp 867–892

Answering why-not and why questions on reverse top-k queries

  • Qing Liu
  • Yunjun Gao
  • Gang Chen
  • Baihua Zheng
  • Linlin Zhou
Regular Paper

DOI: 10.1007/s00778-016-0443-4

Cite this article as:
Liu, Q., Gao, Y., Chen, G. et al. The VLDB Journal (2016) 25: 867. doi:10.1007/s00778-016-0443-4

Abstract

Why-not and why questions can be posed by database users to seek clarifications on unexpected query results. Specifically, why-not questions aim to explain why certain expected tuples are absent from the query results, while why questions try to clarify why certain unexpected tuples are present in the query results. This paper systematically explores the why-not and why questions on reverse top-k queries, owing to its importance in multi-criteria decision making. We first formalize why-not questions on reverse top-k queries, which try to include the missing objects in the reverse top-k query results, and then, we propose a unified framework called WQRTQ to answer why-not questions on reverse top-k queries. Our framework offers three solutions to cater for different application scenarios. Furthermore, we study why questions on reverse top-k queries, which aim to exclude the undesirable objects from the reverse top-k query results, and extend the framework WQRTQ to efficiently answer why questions on reverse top-k queries, which demonstrates the flexibility of our proposed algorithms. Extensive experimental evaluation with both real and synthetic data sets verifies the effectiveness and efficiency of the presented algorithms under various experimental settings.

Keywords

Reverse top-k query Why-not question Why question Result explanation Algorithm 

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Qing Liu
    • 1
  • Yunjun Gao
    • 1
    • 2
  • Gang Chen
    • 1
    • 2
  • Baihua Zheng
    • 3
  • Linlin Zhou
    • 1
  1. 1.College of Computer ScienceZhejiang UniversityHangzhouChina
  2. 2.The Key Lab of Big Data Intelligent Computing of Zhejiang ProvinceZhejiang UniversityHangzhouChina
  3. 3.School of Information SystemsSingapore Management UniversitySingaporeSingapore

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