Skip to main content

Discovering Influential Data Objects over Time

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8098))

Abstract

In applications such as market analysis, it is of great interest to product manufacturers to have their products ranked as highly as possible for a significant number of customers. However, customer preferences change over time, and product manufacturers are interested in monitoring the evolution of the popularity of their products, in order to discover those products that are consistently highly ranked. To take into account the temporal dimension, we define the continuous influential query and present algorithms for efficient processing and retrieval of continuous influential data objects. Furthermore, our algorithms support incremental retrieval of the next continuous influential data object in a natural way. To evaluate the performance of our algorithms, we conduct a detailed experimental study for various setups.

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   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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. Arvanitis, A., Deligiannakis, A., Vassiliou, Y.: Efficient influence-based processing of market research queries. In: Proc. of CIKM, pp. 1193–1202 (2012)

    Google Scholar 

  2. Bernecker, T., Emrich, T., Kriegel, H.-P., Mamoulis, N., Renz, M., Zhang, S., Züfle, A.: Inverse queries for multidimensional spaces. In: Pfoser, D., Tao, Y., Mouratidis, K., Nascimento, M.A., Mokbel, M., Shekhar, S., Huang, Y. (eds.) SSTD 2011. LNCS, vol. 6849, pp. 330–347. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

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

    Google Scholar 

  4. Fagin, R., Lotem, A., Naor, M.: Optimal aggregation algorithms for middleware. In: Proc. of PODS, pp. 102–113 (2001)

    Google Scholar 

  5. Ge, S., Hou, U.L., Mamoulis, N., Cheung, D.W.: Efficient all top-k computation: A unified solution for all top-k, reverse top-k and top-m influential queries. TKDE 25(5), 1015–1027 (2013)

    Google Scholar 

  6. Ilyas, I.F., Beskales, G., Soliman, M.A.: A survey of top-k query processing techniques in relational database systems. ACM Comp. Surv. 40(4) (2008)

    Google Scholar 

  7. Jestes, J., Phillips, J.M., Li, F., Tang, M.: Ranking large temporal data. PVLDB 5(11), 1412–1423 (2012)

    Google Scholar 

  8. Kontaki, M., Papadopoulos, A.N., Manolopoulos, Y.: Continuous top-k dominating queries. TKDE 24(5), 840–853 (2012)

    Google Scholar 

  9. Lee, M.L., Hsu, W., Li, L., Tok, W.H.: Consistent top-k queries over time. In: Zhou, X., Yokota, H., Deng, K., Liu, Q. (eds.) DASFAA 2009. LNCS, vol. 5463, pp. 51–65. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  10. Li, F., Yi, K., Le, W.: Top-k queries on temporal data. VLDB Journal 19(5), 715–733 (2010)

    Article  Google Scholar 

  11. Miah, M., Das, G., Hristidis, V., Mannila, H.: Standing out in a crowd: Selecting attributes for maximum visibility. In: Proc. of ICDE, pp. 356–365 (2008)

    Google Scholar 

  12. Mouratidis, K., Bakiras, S., Papadias, D.: Continuous monitoring of top-k queries over sliding windows. In: Proc. of SIGMOD, pp. 635–646 (2006)

    Google Scholar 

  13. Hou U, L., Mamoulis, N., Berberich, K., Bedathur, S.J.: Durable top-k search in document archives. In: Proc. of SIGMOD, pp. 555–566 (2010)

    Google Scholar 

  14. Vlachou, A., Doulkeridis, C., Kotidis, Y., Nørvåg, K.: Reverse top-k queries. In: Proc. ICDE, pp. 365–376 (2010)

    Google Scholar 

  15. Vlachou, A., Doulkeridis, C., Kotidis, Y., Nørvåg, K.: Monochromatic and bichromatic reverse top-k queries. TKDE 23(8), 1215–1229 (2011)

    Google Scholar 

  16. Vlachou, A., Doulkeridis, C., Nørvåg, K.: Monitoring reverse top-k queries over mobile devices. In: Proc. of MobiDE, pp. 17–24 (2011)

    Google Scholar 

  17. Vlachou, A., Doulkeridis, C., Nørvåg, K., Kotidis, Y.: Identifying the most influential data objects with reverse top-k queries. PVLDB 3(1-2), 364–372 (2010)

    Google Scholar 

  18. Vlachou, A., Doulkeridis, C., Nørvåg, K., Kotidis, Y.: Branch-and-bound algorithm for reverse top-k queries. In: Proc. of SIGMOD (2013)

    Google Scholar 

  19. Wu, T., Sun, Y., Li, C., Han, J.: Region-based online promotion analysis. In: Proc. of EDBT, pp. 63–74 (2010)

    Google Scholar 

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

    Google Scholar 

  21. Yu, A., Agarwal, P.K., Yang, J.: Processing a large number of continuous preference top-k queries. In: Proc. of SIGMOD, pp. 397–408 (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gkorgkas, O., Vlachou, A., Doulkeridis, C., Nørvåg, K. (2013). Discovering Influential Data Objects over Time. In: Nascimento, M.A., et al. Advances in Spatial and Temporal Databases. SSTD 2013. Lecture Notes in Computer Science, vol 8098. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40235-7_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40235-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40234-0

  • Online ISBN: 978-3-642-40235-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics