Answering the Why-Not Questions of Graph Query Autocompletion

  • Guozhong Li
  • Nathan Ng
  • Peipei Yi
  • Zhiwei Zhang
  • Byron Choi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10827)

Abstract

Graph query autocompletion (gQAC) helps users formulate graph queries in a visual environment (a.k.a GUI). It takes a graph query that the user is formulating as input and generates a ranked list of query suggestions. Since it is impossible to accurately predict the user’s target query, the current state-of-the-art of gQAC sometimes fails to produce useful suggestions. In such scenarios, it is natural for the user to ask why are useful suggestions not returned. In this paper, we address the why-not questions of gQAC. Specifically, given an intermediate query q, a target query \(q_t\), and a gQAC system X, the why-not questions of gQAC seek for the minimal refinement of the configuration of X, with respect to a penalty model, such that at least one useful suggestion towards \(q_t\) appears in the returned suggestions. We propose a generic ranking function for existing gQAC systems. We propose a search algorithm for the why-not questions.

Keywords

Graph query Query autocompletion Why-not questions 

References

  1. 1.
    Chapman, A., Jagadish, H.V.: Why not? In: SIGMOD, pp. 523–534 (2009)Google Scholar
  2. 2.
    Islam, M.S., Liu, C., Li, J.: Efficient answering of why-not questions in similar graph matching. TKDE 27, 2672–2686 (2015)Google Scholar
  3. 3.
    Jayaram, N., Goyal, S., Li, C.: VIIQ: auto-suggestion enabled visual interface for interactive graph query formulation. PVLDB 8, 1940–1951 (2015)Google Scholar
  4. 4.
    Li, G., Ng, N., Yi, P., Zhang, Z., Choi, B.: Answering the why-not questions of graph query autocompletion (2018). https://goo.gl/4Hpt5m
  5. 5.
    Mottin, D., Bonchi, F., Gullo, F.: Graph query reformulation with diversity. In: KDD, pp. 825–834 (2015)Google Scholar
  6. 6.
    Nandi, A., Jagadish, H.V.: Effective phrase prediction. In: PVLDB, pp. 219–230 (2007)Google Scholar
  7. 7.
  8. 8.
    Pienta, R., Hohman, F., Tamersoy, A., Endert, A., Navathe, S., Tong, H., Chau, D.H.: Visual graph query construction and refinement. In: SIGMOD, pp. 1587–1590 (2017)Google Scholar
  9. 9.
    Yi, P., Choi, B., Bhowmick, S., Xu, J.: AutoG: a visual query autocompletion framework for graph databases. VLDB J. 26, 347–372 (2017)CrossRefGoogle Scholar
  10. 10.
    Yi, P., Choi, B., Zhang, Z., Bhowmick, S.S., Xu, J.: Gfocus: user focus-based graph query autocompletion (2018). https://goo.gl/MYYw94

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Guozhong Li
    • 1
  • Nathan Ng
    • 1
  • Peipei Yi
    • 1
  • Zhiwei Zhang
    • 1
  • Byron Choi
    • 1
  1. 1.Department of Computer ScienceHong Kong Baptist UniversityKowloon TongHong Kong

Personalised recommendations