Skip to main content

Discovering the Most Potential Stars in Social Networks with Infra-skyline Queries

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7235))

Abstract

With the rapid development of Social Network (SN for short), people increasingly pay attention to the importance of the roles which they play in the SNs. As is usually the case, the standard for measuring the importance of the members is multi-objective. The skyline operator is thus introduced to distinguish the important members from the entire community. For decision-making, people are interested in the most potential members which can be promoted into the skyline with minimum cost, namely the problem of Member Promotion in Social Networks. In this paper, we propose some interesting new concepts such as Infra-Skyline and Promotion Boundary, and then we exploit a novel promotion boundary based approach, i.e., the InfraSky algorithm. Extensive experiments on both real and synthetic datasets are conducted to show the effectiveness and efficiency of the InfraSky algorithm.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Börzsönyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: ICDE, pp. 421–430 (2001)

    Google Scholar 

  2. Chen, L., Lian, X.: Dynamic skyline queries in metric spaces. In: EDBT, pp. 333–343 (2008)

    Google Scholar 

  3. Deng, K., Zhou, X., Shen, H.T.: Multi-source skyline query processing in road networks. In: ICDE, pp. 796–805 (2007)

    Google Scholar 

  4. Fuhry, D., Jin, R., Zhang, D.: Efficient skyline computation in metric space. In: EDBT, pp. 1042–1051 (2009)

    Google Scholar 

  5. Jang, S., Park, C., Yoo, J.: Skyline Minimum Vector. In: APWeb, pp. 358–360 (2010)

    Google Scholar 

  6. Jin, W., Han, J., Ester, M.: Mining Thick Skylines over Large Databases. In: Boulicaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.) PKDD 2004. LNCS (LNAI), vol. 3202, pp. 255–266. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  7. Kossmann, D., Ramsak, F., Rost, S.: Shooting stars in the sky: An online algorithm for skyline queries. In: VLDB, pp. 275–286 (2002)

    Google Scholar 

  8. Kung, H., Luccio, F., Preparata, F.: On finding the maxima of a set of vectors. Journal of the ACM (JACM) 22(4), 469–476 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  9. Papadias, D., Tao, Y., Fu, G., Seeger, B.: An optimal and progressive algorithm for skyline queries. In: SIGMOD, pp. 467–478 (2003)

    Google Scholar 

  10. Papadias, D., Tao, Y., Fu, G., Seeger, B.: Progressive skyline computation in database systems. ACM TODS 30(1), 41–82 (2005)

    Article  Google Scholar 

  11. Peng, Z., Wang, C., Han, L., Hao, J., Bai, Y.: Discovering the Most Potential Stars in Social Networks. In: Proceedings of the Third International Conference on Emerging Databases, Incheon, Korea (August 2011)

    Google Scholar 

  12. Sharifzadeh, M., Shahabi, C.: The spatial skyline queries. In: VLDB, pp. 751–762 (2006)

    Google Scholar 

  13. Tan, K.-L., Eng, P.-K., Ooi, B.C.: Efficient progressive skyline computation. In: VLDB, pp. 301–310 (2001)

    Google Scholar 

  14. Wu, T., Xin, D., Mei, Q., Han, J.: Promotion analysis in multi-dimensional space. PVLDB 2(1), 109–120 (2009)

    Google Scholar 

  15. Zou, L., Chen, L., Özsu, M.T., Zhao, D.: Dynamic Skyline Queries in Large Graphs. In: Kitagawa, H., Ishikawa, Y., Li, Q., Watanabe, C. (eds.) DASFAA 2010. LNCS, vol. 5982, pp. 62–78. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Peng, Z., Wang, C., Han, L., Hao, J., Ou, X. (2012). Discovering the Most Potential Stars in Social Networks with Infra-skyline Queries. In: Sheng, Q.Z., Wang, G., Jensen, C.S., Xu, G. (eds) Web Technologies and Applications. APWeb 2012. Lecture Notes in Computer Science, vol 7235. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29253-8_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29253-8_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29252-1

  • Online ISBN: 978-3-642-29253-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics