Answering Why-Not Questions on Structural Graph Clustering

  • Chuanyu Zong
  • Xiufeng Xia
  • Bin Wang
  • Xiaochun Yang
  • Jiajia Li
  • Xiangyu Liu
  • Rui Zhu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10827)


Structural graph clustering is one fundamental problem in managing and analyzing graph data. As a fast and exact density based graph clustering algorithm, pSCAN is widely used to discover meaningful clusters in many different graph applications. The problem of explaining why-not questions on pSCAN is to find why an expected vertex is not included in the specified cluster of the pSCAN results. Obviously, the pSCAN results are sensitive to two parameters: (i) the similarity threshold \(\epsilon \); and (ii) the density constraint \(\mu \), when them are not set good enough, some expected vertices would be missing in the specified clusters. To tackle this problem, we firstly analyze that how the parameters affect the results of pSCAN, then we propose two novel explanation algorithms to explain why-not questions on pSCAN by offering some advices on how to refine the initial pSCAN with minimum penalty from two perspectives: (i) modifying the parameter \(\epsilon \); and (ii) modifying the parameter \(\mu \). Moreover, we present some constraints to ensure the original pSCAN results are retained as much as possible in the results of refined pSCAN. Finally, we conduct comprehensive experimental studies, which show that our approaches can efficiently return high-quality explanations for why-not questions on pSCAN.


Why-not question pSCAN Query refinement Explanation 



The work is supported by the National Natural Science Foundation of China (Nos. U1736104, 61572122, 61532021, 61502317, 61502316, 61702344).


  1. 1.
    Chapman, A., Jagadish, H.V.: Why not‘?’. In: SIGMOD, pp. 523–534 (2009)Google Scholar
  2. 2.
    Chang, L., Li, W., Lin, X., Qin, L., Zhang, W.: pSCAN: fast and exact structural graph clustering. In: ICDE, pp. 253–264 (2016)Google Scholar
  3. 3.
    Xu, X., Yuruk, N., Feng, Z., Schweiger, T.A.J.: SCAN: a structural clustering algorithm for networks. In: KDD, pp. 824–833 (2007)Google Scholar
  4. 4.
    Shiokawa, H., Fujiwara, Y., Onizuka, M.: SCAN++: efficient algorithm for finding clusters, hubs and outliers on large-scale graphs. In: PVLDB, pp. 1178–1189 (2015)CrossRefGoogle Scholar
  5. 5.
    Huang, J., Chen, T., Doan, A., Naughton. J.F.: On the provenance of non-answers to queries over extracted data. In: PVLDB, pp. 736–747 (2008)CrossRefGoogle Scholar
  6. 6.
    Zong, C., Yang, X., Wang, B., Liu, C.: Minimal explanations of missing values by chasing acquisitional data. WWWJ 20, 1333–1362 (2017). Scholar
  7. 7.
    Zong, C., Yang, X., Wang, B., Zhang, J.: Minimizing explanations for missing answers to queries on databases. In: Meng, W., Feng, L., Bressan, S., Winiwarter, W., Song, W. (eds.) DASFAA 2013. LNCS, vol. 7825, pp. 254–268. Springer, Heidelberg (2013). Scholar
  8. 8.
    Herschel, M., Hernández, M.A., Tan, W.C.: Artemis: a system for analyzing missing answers. In: PVLDB, pp. 1550–1553 (2009)CrossRefGoogle Scholar
  9. 9.
    Herschel, M., Hernández, M.A.: Explaining missing answers to SPJUA queries. In: PVLDB, pp. 185–196 (2010)CrossRefGoogle Scholar
  10. 10.
    Tran, Q.T., Chan, C.Y.: How to ConQueR why-not questions. In: SIGMOD, pp. 15–26 (2010)Google Scholar
  11. 11.
    He, Z., Lo, E.: Answering why-not questions on top-k queries. In: ICDE, pp. 750–761 (2012)Google Scholar
  12. 12.
    Liu, Q., Gao, Y., Chen, G., Zheng, B., Zhou, L.: Answering why-not and why questions on reverse top-k queries. VLDB J. 25, 867–892 (2016)CrossRefGoogle Scholar
  13. 13.
    Chen, L., Lin, X., Hu, H., Jensen, C.S., Xu, J.L: Answering why-not spatial keyword top-k queries via keyword adaption. In: ICDE, pp. 697–708 (2016)Google Scholar
  14. 14.
    Islam, M.S., Zhou, R., Liu, C.: On answering why-not questions in reverse skyline queries. In: ICDE, pp. 973–984 (2013)Google Scholar
  15. 15.
    Islam, M.S., Liu, C., Li, J.: Efficient answering of why-not questions in similar graph matching. TKDE 27, 2672–2686 (2015)Google Scholar
  16. 16.
    Roy, S., Suciu, D.: A formal approach to finding explanations for database queries. In: SIGMOD, pp. 1579–1590 (2014)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Chuanyu Zong
    • 1
  • Xiufeng Xia
    • 1
  • Bin Wang
    • 2
  • Xiaochun Yang
    • 2
  • Jiajia Li
    • 1
  • Xiangyu Liu
    • 1
  • Rui Zhu
    • 1
  1. 1.College of Computer ScienceShenyang Aerospace UniversityLiaoningChina
  2. 2.School of Computer Science and EngineeringNortheastern UniversityLiaoningChina

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