TopCom: Index for Shortest Distance Query in Directed Graph

  • Vachik S. Dave
  • Mohammad Al Hasan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9261)


Finding shortest distance between two vertices in a graph is an important problem due to its numerous applications in diverse domains, including geo-spatial databases, social network analysis, and information retrieval. Classical algorithms (such as, Dijkstra) solve this problem in polynomial time, but these algorithms cannot provide real-time response for a large number of bursty queries on a large graph. So, indexing based solutions that pre-process the graph for efficiently answering (exactly or approximately) a large number of distance queries in real-time are becoming increasingly popular. Existing solutions have varying performance in terms of index size, index building time, query time, and accuracy. In this work, we propose TopCom, a novel indexing-based solution for exactly answering distance queries in a directed acyclic graph (DAG). Our experiments with two of the existing state-of-the-art methods (IS-Label and TreeMap) show the superiority of TopCom over these two methods considering scalability and query time.


Shortest distance query Indexing method for distance query Directed acyclic graph 



This research is supported by M. Hasan’s NSF CAREER award (IIS-1149851)


  1. 1.
    Akiba, T., Iwata, Y., Yoshida, Y.: Fast exact shortest-path distance queries on large networks by pruned landmark labeling. In: ACM SIGMOD, pp. 349–360 (2013)Google Scholar
  2. 2.
    Backstrom, L., Huttenlocher, D., Kleinberg, J., Lan, X.: Group formation in large social networks: membership, growth, and evolution. In: SIGMOD, pp. 44–54 (2006)Google Scholar
  3. 3.
    Cheng, J., Huang, S., Wu, H., Fu, A.W.C.: TF-Label: a topological-folding labeling scheme for reachability querying in a large graph. In: SIGMOD, pp. 193–204 (2013)Google Scholar
  4. 4.
    Cohen, E., Halperin, E., Kaplan, H., Zwick, U.: Reachability and distance queries via 2-hop labels. In: SODA, pp. 937–946 (2002)Google Scholar
  5. 5.
    Fu, A.W.C., Wu, H., Cheng, J., Wong, R.C.W.: IS-Label: an independent-set based labeling scheme for point-to-point distance querying. VLDB 6, 457–468 (2013)Google Scholar
  6. 6.
    Hasan, M., Zaki, M.: A survey of link prediction in social networks. In: Aggarwal, C.C. (ed.) Social Network Data Analytics, pp. 243–275. Springer, US (2011)CrossRefGoogle Scholar
  7. 7.
    Jin, R., Ruan, N., Xiang, Y., Lee, V.: A highway-centric labeling approach for answering distance queries on large sparse graphs. In: SIGMOD, pp. 445–456 (2012)Google Scholar
  8. 8.
    Kargar, M., An, A.: Keyword search in graphs: Finding r-cliques. Proc. VLDB Endow. 4(10), 681–692 (2011)CrossRefGoogle Scholar
  9. 9.
    Massa, P., Avesani, P.: Trust-aware bootstrapping of recommender systems. In: ECAI Workshop on Recommender Systems, pp. 29–33 (2006)Google Scholar
  10. 10.
    Okamoto, K., Chen, W., Li, X.-Y.: Ranking of closeness centrality for large-scale social networks. In: Preparata, F.P., Wu, X., Yin, J. (eds.) FAW 2008. LNCS, vol. 5059, pp. 186–195. Springer, Heidelberg (2008) CrossRefGoogle Scholar
  11. 11.
    Qiao, M., Cheng, H., Chang, L., Yu, J.: Approximate shortest distance computing: a query-dependent local landmark scheme. IEEE Trans. Knowl. Data Eng. 26(1), 55–68 (2014)CrossRefGoogle Scholar
  12. 12.
    Xiang, Y.: Answering exact distance queries on real-world graphs with bounded performance guarantees. VLDB J. 23(5), 677–695 (2014)CrossRefGoogle Scholar
  13. 13.
    Yan, D., Cheng, J., Ng, W., Liu, S.: Finding distance-preserving subgraphs in large road networks. In: ICDE, pp. 625–636 (2013)Google Scholar
  14. 14.
    Yildirim, H., Chaoji, V., Zaki, M.: Grail: a scalable index for reachability queries in very large graphs. VLDB J. 21(4), 509–534 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computer and Information ScienceIndiana University Purdue University IndianapolisIndianapolisUSA

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