Skip to main content

K-Nearest Neighbor Search for Moving Query Point

  • Conference paper
  • First Online:
Advances in Spatial and Temporal Databases (SSTD 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2121))

Included in the following conference series:

Abstract

This paper addresses the problem of finding k nearest neighbors for moving query point (we call it k-NNMP). It is an important issue in both mobile computing research and real-life applications. The problem assumes that the query point is not static, as in k-nearest neighbor problem, but varies its position over time. In this paper, four different methods are proposed for solving the problem. Discussion about the parameters affecting the performance of the algorithms is also presented. A sequence of experiments with both synthetic and real point data sets are studied. In the experiments, our algorithms always outperform the existing ones by fetching 70% less disk pages. In some settings, the saving can be as much as one order of magnitude.

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 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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. S. Berchtold, B. Ertl, D. Keim, H. Kriegel, and T. Seidl. Fast nearest neighbor search in high-dimensional space. In Proceedings of International Conference on Data Engineering, Orlando, USA, 1998.

    Google Scholar 

  2. U. C. Bereau. Tiger(r) topologically integrated geographic encoding and referencing system, 1998.

    Google Scholar 

  3. S. Chaudhuri and L. Gravona. Evaluating top-k selection queries. In Proceedings of International Conference on Very Large Database, Edinburgh, Scotland, 1999.

    Google Scholar 

  4. A. Corral, Y. Manolopoulos, Y. Theodoridis, and M. Vassilakopoulos. Closest pair queries in spatial databases. In Proceedings of ACM SIGMOD International Conference on Management of Data, Dallas, USA, 2000.

    Google Scholar 

  5. M. de Berg, M. van Dreveld, M. Overmars, and O. Schwarzkop. Computational Geometry: Algorithms and Applications. Springer-Verlag, 1997.

    Google Scholar 

  6. U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy. Advances in Knowledge Discovery and Data Mining. AAAI Press/MIT Press, 1996.

    Google Scholar 

  7. V. Gaede and O. Guenther. Multidimensional access methods. ACM Computer Surveys, 30, 1998.

    Google Scholar 

  8. T. Kanungu, D. Mount, N. Netanyahu, C. Piatko, R. Silverman, and A. Wu. Computing nearest neighbors for moving points and applications to clustering. In Proceedings of 10th ACM-SIAM Symposium on Discrete Algorithms, 1999.

    Google Scholar 

  9. F. Korn, N. Sidiropoulos, C. Faloutsos, E. Siegel, and Z. Protopapas. Fast nearest neighbor search in medical image databases. In Proceedings of International Conference on Very Large Database, Mumbai, India, 1996.

    Google Scholar 

  10. H. Kriegel. S3: Similarity search in cad database systems. In Proceedings of ACM SIGMOD International Conference on Management of Data, Tucson, USA, 1997.

    Google Scholar 

  11. A. Papadopoulos and Y. Manolopoulos. Performance of nearest neighbor queries in r-trees. In Proceedings of International Conference on Database Theory, Delphi, Greece, 1997.

    Google Scholar 

  12. D. Pfoser and C. Jensen. Capturing the uncertainty of moving-object representations. In Proceedings of International Symposium on Large Spatial Databases, 1999.

    Google Scholar 

  13. N. Roussopoulos, S. Kelley, and F. Vincent. Nearest neighbor queries. In Proceedings of ACM SIGMOD International Conference on Management of Data, San Jose, USA, 1995.

    Google Scholar 

  14. T. Seidl and H. Kriegel. Optimal multi-step k-nearest neighbor search. In Proceedings of ACM SIGMOD International Conference on Management of Data, Seattle, USA, 1998.

    Google Scholar 

  15. T. Seidl and H. Kriegel. Efficient user-adaptable similarity search in large multimedia database. In Proceedings of International Conference on Very Large Database, Athens, Greece, Athens.

    Google Scholar 

  16. P. Sistla and O. Wolfson. Research issues in moving objects database. In Proceedings of ACM SIGMOD International Conference on Management of Data, Dallas, USA, 2000.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Song, Z., Roussopoulos, N. (2001). K-Nearest Neighbor Search for Moving Query Point. In: Jensen, C.S., Schneider, M., Seeger, B., Tsotras, V.J. (eds) Advances in Spatial and Temporal Databases. SSTD 2001. Lecture Notes in Computer Science, vol 2121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47724-1_5

Download citation

  • DOI: https://doi.org/10.1007/3-540-47724-1_5

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42301-0

  • Online ISBN: 978-3-540-47724-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics