Skip to main content

Graph Mining on Streams

  • Reference work entry
Book cover Encyclopedia of Database Systems

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 2,500.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Recommended Reading

  1. Aggarwal G., Datar M., Rajagopalan S., and Ruhl M. On the streaming model augmented with a sorting primitive. IEEE Symposium on Foundations of Computer Science, 2004, pp. 540–549.

    Google Scholar 

  2. Bar-Yossef Z., Kumar R., and Sivakumar D. Reductions in streaming algorithms, with an application to counting triangles in graphs. In ACM-SIAM Symp. on Discrete Algorithms, 2002, pp. 623–632.

    Google Scholar 

  3. Buchsbaum A.L., Giancarlo R., and Westbrook J. On finding common neighborhoods in massive graphs. Theor. Comput. Sci., 1–3(299):707–718, 2003.

    Article  MathSciNet  Google Scholar 

  4. Buriol L.S., Frahling G., Leonardi S., Marchetti-Spaccamela A., and Sohler C. Counting triangles in data streams. In Proc. 25th ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems, 2006, pp. 253–262.

    Google Scholar 

  5. Chakrabarti A., Cormode G., and McGregor A. A near-optimal algorithm for computing the entropy of a stream. In ACM-SIAM Symposium on Discrete Algorithms, 2007, pp. 328–335.

    Google Scholar 

  6. Cormode G. and Muthukrishnan S. Space efficient mining of multigraph streams. In Proc. 24th ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems, 2005, pp. 271–282.

    Google Scholar 

  7. Das Sarma A., Gollapudi S., and Panigrahy R. Estimating PageRank on graph streams. In Proc. 27th ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems, 2008, pp. 69–78.

    Google Scholar 

  8. Demetrescu C., Escoffier B., Moruz G., and Ribichini A. Adapting parallel algorithms to the w-stream model, with applications to graph problems. In Mathematical Foundations of Computer Science, 2007, pp. 194–205.

    Google Scholar 

  9. Demetrescu C., Finocchi I., and Ribichini A. Trading off space for passes in graph streaming problems. In ACM-SIAM Symposium on Discrete Algorithms, 2006, pp. 714–723.

    Google Scholar 

  10. Elkin M. Streaming and fully dynamic centralized algorithms for constructing and maintaining sparse spanners. In Int. Colloquium on Automata, Languages and Programming, 2007, pp. 716–727.

    Google Scholar 

  11. Elkin M. and Zhang J. Efficient algorithms for constructing (1 + ε, β)-spanners in the distributed and streaming models. Distrib. Comput., 18(5):375–385, 2006.

    Article  Google Scholar 

  12. Feigenbaum J., Kannan S., McGregor A., Suri S., and Zhang J. Graph distances in the data-stream model. SIAM J. Comput., 38(5):1708–1727, 2008.

    Google Scholar 

  13. Feigenbaum J., Kannan S., McGregor A., Suri S., and Zhang J. On graph problems in a semi-streaming model. Theor. Comput. Sci., 348(2–3):207–216, 2005.

    Article  MATH  MathSciNet  Google Scholar 

  14. Ganguly S. and Saha B. On estimating path aggregates over streaming graphs. In Int. Symp. on Algorithms and Computation, 2006, pp. 163–172.

    Google Scholar 

  15. Henzinger M.R., Raghavan P., and Rajagopalan S. Computing on data streams. External memory algorithms, 1999, pp. 107–118.

    Google Scholar 

  16. McGregor A. Finding graph matchings in data streams. In APPROX-RANDOM, 2005, pp. 170–181.

    Google Scholar 

  17. Muthukrishnan S. Data Streams: Algorithms and Applications. Foundations and Trends in Theoretical Computer Science, 1(2), 2005.

    Google Scholar 

  18. Zelke M. k-connectivity in the semi-streaming model. CoRR, cs/0608066, 2006.

    Google Scholar 

  19. Zelke M. Weighted matching in the semi-streaming model. In Proc. Symp. on Theoretical Aspects of Computer Science, 2008.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this entry

Cite this entry

McGregor, A. (2009). Graph Mining on Streams. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_184

Download citation

Publish with us

Policies and ethics