Skip to main content
SpringerLink
Log in

Constrained Nearest Neighbor Queries

  • 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

In this paper we introduce the notion of constrained nearest neighbor queries (CNN) and propose a series of methods to answer them. This class of queries can be thought of as nearest neighbor queries with range constraints. Although both nearest neighbor and range queries have been analyzed extensively in previous literature, the implications of constrained nearest neighbor queries have not been discussed. Due to their versatility, CNN queries are suitable to a wide range of applications from GIS systems to reverse nearest neighbor queries and multimedia applications. We develop methods for answering CNN queries with different properties and advantages. We prove the optimality (with respect to I/O cost) of one of the techniques proposed in this paper. The superiority of the proposed technique is shown by a performance analysis.

This work was partially supported by NSF grant EIA98-18320, IIS98-17432 and IIS99-70700.

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

Access this chapter

Log in via an institution
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. P. Bernstein, M. Brodie, S. Ceri, D. DeWitt, M. Franklin, H. Garcia-Molina, J. Gray, J. Held, J. Hellerstein, H. Jagadish, M. Lesk, D. Maier, J. Naughton, H. Pirahesh, M. Stonebraker, and J. Ullman. The Asilomar report on database research. ACM Sigmod Record, 27(4), December 1998.

    Google Scholar 

  2. S. Berchtold, C. Bohm, and H.-P. Kriegel. The Pyramid-Technique: Towards breaking the curse of dimensionality. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 142–153, Seattle, Washington, USA, June 1998.

    Google Scholar 

  3. S. Berchtold, C. Bohm, D. Keim, and H. Kriegel. A cost model for nearest neighbor search in high-dimensional data space. In Proc. ACM Symp. on Principles of Database Systems, pages 78–86, Tuscon, Arizona, June 1997.

    Google Scholar 

  4. S. Berchtold, D. A. Keim, and H. P. Kriegel. The x-tree: An index structure for high-dimensional data. In Proceedings of the 22nd International Conference on Very Large Databases (VLDB), pages 28–36, 1996.

    Google Scholar 

  5. N. Beckmann, H. P. Kriegel, R. Schneider, and B. Seeger. The r*-tree: An efficient and robust access method for points and reactangles. In Proceedings of the ACM SIGMOD International Conference on Management of Data, pages 322–331, May 1990.

    Google Scholar 

  6. X. Cheng, R. Dolin, M. Neary, S. Prabhakar, K. Ravikanth, D. Wu, D. Agrawal, A. El Abbadi, M. Freeston, A. Singh, T. Smith, and J. Su. Scalable access within the context of digital libraries. In IEEE Proceedings of the International Conference on Advances in Digital Libraries, ADL, pages 70–81, Washington, D.C., 1997.

    Google Scholar 

  7. M. Ester, J. Kohlhammer, and H. P. Kriegel. The dc-tree: a fully dynamic index structure for data warehouses. In Proceedings of the 16th International Conference on Data Engineering (ICDE), March 2000.

    Google Scholar 

  8. H. Ferhatosmanoglu, D. Agrawal, and A. El Abbadi. Clustering declus-tered data for efficient retrieval. In Proc. Conf. on Information and Knowledge Management, pages 343–350, Kansas City, Missouri, November 1999.

    Google Scholar 

  9. H. Ferhatosmanoglu, D. Agrawal, and A. El Abbadi. Concentric hyper-spaces and disk allocation for fast parallel range searching. In Proc. Int. Conf. Data Engineering, pages 608–615, Sydney, Australia, March 1999.

    Google Scholar 

  10. H. Ferhatosmanoglu, E. Tuncel, D. Agrawal, and A. El Abbadi. Approximate nearest neighbor searching in multimedia databases. In Proc of 17th IEEE Int. Conf. on Data Engineering (ICDE), pages 503–511, Heidelberg, Germany, April 2001.

    Google Scholar 

  11. J. D. Foley, A. Van Dam, S. K. Feiner, and J. F. Hughes. Computer Graphics: Principles and Practice. Addison Wesley, 1996.

    Google Scholar 

  12. V. Gaede and O. Gunther. Multidimensional access methods. ACM Computing Surveys, 30:170–231, 1998.

    Article  Google Scholar 

  13. A. Gionis, P. Indyk, and R. Motwani. Similarity searching in high dimensions via hashing. In Proceedings of the Int. Conf. on Very Large Data Bases, pages 518–529, Edinburgh, Scotland, UK, September 1999.

    Google Scholar 

  14. A. Guttman. R-trees: A dynamic index structure for spatial searching. In Proceedings of the ACM SIGMOD International Conference on Management of Data, pages 47–57, June 1984.

    Google Scholar 

  15. G. R. Hjaltason and H. Samet. Ranking in spatial databases. In Proc. of 4th Int. Symp. on Large Spatial Databases, pages 83–95, Portland,ME, 1995.

    Google Scholar 

  16. G. Hjaltason and H. Samet. Distance browsing in spatial databases. ACM Transactions on Database Systems, 24(2):265–318, 1999.

    Article  Google Scholar 

  17. I. Kamel and C. Faloutsos. On packing r-trees. In Proceedings of the 2nd International Conference on Information and Knowledge Management (CIKM), pages 490–499, 1993.

    Google Scholar 

  18. I. Kamel and C. Faloutsos. Hilbert r-tree: An improved r-tree using fractals. In Proceedings of the International Conference on Very Large Databases, September 1994.

    Google Scholar 

  19. F. Korn and S. Muthukrishnan. Influence sets based on reverse nearest neighbor queries. In Proc. ACM SIGMOD Int. Conf. on Management of Data, Dallas, USA, May 2000.

    Google Scholar 

  20. D. B. Lomet and B. Salzberg. The hb-tree: A multi-attribute indexing method with good guaranteed performance. ACM Transactions on Database Systems, 15(4):625–658, December 1990.

    Google Scholar 

  21. B. S. Manjunath. Airphoto dataset. http://vivaldi.ece.ucsb.edu/Manjunath/research.htm, May 2000.

  22. B. S. Manjunath and W. Y. Ma. Texture features for browsing and retrieval of image data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(8):837–42, August 1996.

    Google Scholar 

  23. J. Nievergelt, H. Hinterberger, and K.C. Sevcik. The grid file: an adaptable, symmetric multikey file structure. ACM Transactions on Database Systems 9,1:38–71, March 1984.

    Google Scholar 

  24. G. Proietti and C. Faloutsos. I/o complexity for range queries on region data stored using an r-tree. In Proceedings of the International Conference on Data Engineering (ICDE), March 1999.

    Google Scholar 

  25. N. Roussopoulos, S. Kelly, and F. Vincent. Nearest neighbor queries. In Proceedings of the ACM SIGMOD International Conference on Management of Data, pages 71–79, May 1995.

    Google Scholar 

  26. J. T. Robinson. The kdb-tree: A search structure for large multidimensional dynamic indexes. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 10–18, 1981.

    Google Scholar 

  27. I. Stanoi, D. Agrawal, and A. El Abbadi. Reverse nearest neighbor queries for dynamic databases. In Proceedings of the ACM SIGMOD Workshop on Data Mining and Knowledge Discovery (DMKD), 2000.

    Google Scholar 

  28. H. Samet. The Design and Analysis of Spatial Structures. Addison Wesley Publishing Company, Inc., Massachusetts, 1989.

    Google Scholar 

  29. T. Sellis and N. Roussopoulos. The r+-tree: A dynamic index for multidimensional objects. In Proceedings of the 13th International Conference on Very Large Databases (VLDB), pages 507–518, May 1987.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Department, University of California at Santa Barbara, USA

    Hakan Ferhatosmanoglu, Ioanna Stanoi, Divyakant Agrawal & Amr El Abbadi

Authors
  1. Hakan Ferhatosmanoglu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ioanna Stanoi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Divyakant Agrawal
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Amr El Abbadi
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, Aalborg University, Fredrik Bajers Vej 7E, 9220, Aalborg Øst, Denmark

    Christian S. Jensen

  2. Praktische Informatik IV, FernUniversität Hagen, 58084, Hagen, Germany

    Markus Schneider

  3. Fachbereich Mathematik und Informatik, Philipps-Universität Marburg, 35032, Marburg, Germany

    Bernhard Seeger

  4. Department of Computer Science and Engineering, University of California, Riverside, CA, 92521, USA

    Vassilis J. Tsotras

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ferhatosmanoglu, H., Stanoi, I., Agrawal, D., El Abbadi, A. (2001). Constrained Nearest Neighbor Queries. 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_14

Download citation

  • DOI: https://doi.org/10.1007/3-540-47724-1_14

  • 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

Search

Navigation