Similarity Join in Metric Spaces Using eD-Index

  • Vlastislav Dohnal
  • Claudio Gennaro
  • Pavel Zezula
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2736)


Similarity join in distance spaces constrained by the metric postulates is the necessary complement of more famous similarity range and the nearest neighbor search primitives. However, the quadratic computational complexity of similarity joins prevents from applications on large data collections. We present the eD-Index, an extension of D-index, and we study an application of the eD-Index to implement two algorithms for similarity self joins, i.e. the range query join and the overloading join. Though also these approaches are not able to eliminate the intrinsic quadratic complexity of similarity joins, significant performance improvements are confirmed by experiments.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Chavez, E., Navarro, G., Baeza-Yates, R., Marroquin, J.: Searching in Metric Spaces. ACM Computing Surveys 33(3), 273–321 (2001)CrossRefGoogle Scholar
  2. 2.
    Dohnal, V., Gennaro, C., Savino, P., Zezula, P.: D-Index: Distance Searching Index for Metric Data Sets. In: ACM Multimedia Tools and Applications 21(1) (September 2003) (to appear)Google Scholar
  3. 3.
    Dohnal, V., Gennaro, C., Zezula, P.: A Metric Index for Approximate Text Management. In: Proceedings of IASTED International Conference on Information Systems and Databases (ISDB 2002), Tokyo, Japan, pp. 37–42 (2002)Google Scholar
  4. 4.
    Galhardas, H., Florescu, D., Shasha, D., Simon, E., Saita, C.A.: Declarative Data Cleaning: Language, Model, and Algorithms. In: Proceedings of the 27th VLDB Conference, Rome, Italy, pp. 371–380 (2001)Google Scholar
  5. 5.
    Gennaro, C., Savino, P., Zezula, P.: Similarity Search in Metric Databases through Hashing. In: Proceedings of ACM Multimedia 2001 Workshops, Ottawa, Canada, pp. 1–5 (October 2001)Google Scholar
  6. 6.
    Gravano, L., Ipeirotis, P.G., Jagadish, H.V., Koudas, N., Muthukrishnan, S., Srivastava, D.: Approximate String Joins in a Database (Almost) for Free. In: Proceedings of the 27th VLDB Conference, Rome, Italy, pp. 491–500 (2001)Google Scholar
  7. 7.
    Guha, S., Jagadish, H.V., Koudas, N., Srivastava, D., Yu, T.: Approximate XML Joins. In: Proceedings of ACM SIGMOD 2002, Madison,Wisconsin, June 3–6 (2002)Google Scholar
  8. 8.
    Kukich, K.: Techniques for automatically correcting words in text. ACM Computing Surveys 24(4), 377–439 (1992)CrossRefGoogle Scholar
  9. 9.
    Navarro, G.: A guided tour to approximate string matching. ACM Computing Surveys 33(1), 31–88 (2001)CrossRefGoogle Scholar
  10. 10.
    Yianilos, P.N.: Excluded Middle Vantage Point Forests for Nearest Neighbor Search. Tech. rep., NEC Research Institute, 1999, Presented at Sixth DIMACS Implementation Challenge: Nearest Neighbor Searches workshop, January 15 (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Vlastislav Dohnal
    • 1
  • Claudio Gennaro
    • 2
  • Pavel Zezula
    • 1
  1. 1.Masaryk UniversityBrnoCzech Republic
  2. 2.ISTI-CNRPisaItaly

Personalised recommendations