Large-Scale Similarity-Based Join Processing in Multimedia Databases

  • Harald Kosch
  • Andreas Wölfl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7131)


This paper presents efficient parallelization strategies for processing large-scale multimedia database operations. These strategies are implemented by extending and parallelizing the GiST (Generalized Search Tree)-framework. Both data and pipeline parallelism strategies are used to execute multi join operations. We integrate the parallelized framework into an Oracle 11g Multimedia Database using its extension mechanisms. Our strategies and their implementations are tested and validated with real and random data sets consisting of up-to 10 millions of image objects.


Multimedia Databases Similarity-based Operations Parallel Processing 


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  1. 1.
    Lew, M.S., Sebe, N., Djerba, C., Jain, R.: Content-based multimedia information retrieval: State-of-the-art and challenges. ACM Transactions on Multimedia Computing, Communications, and Applications 2(1), 1–19 (2006)CrossRefGoogle Scholar
  2. 2.
    Datta, R., Joshi, D., Li, J., Wang, J.Z.: Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys 40(2), 1–60 (2008)CrossRefGoogle Scholar
  3. 3.
    Kosch, H., Atnafu, S.: Processing a multimedia join through the method of nearest neighbor search. Inf. Process. Lett. 82(5), 269–276 (2002)CrossRefzbMATHGoogle Scholar
  4. 4.
    Yu, C., Cui, B., Wang, S., Su, J.: Efficient index-based knn join processing for high-dimensional data. Information and Software Technology 49, 332–344 (2007)CrossRefGoogle Scholar
  5. 5.
    Kosch, H.: Optimizing similarity-based image joins in a multimedia database. In: Proceedings of the ACM International Workshop on Very-Large-Scale Multimedia Corpus, Mining and Retrieval, VLS-MCMR 2010, pp. 37–42. ACM (2010)Google Scholar
  6. 6.
    Samet, H.: Foundations of Multidimensional and Metric Data Structures. Morgan Kaufmann (2006)Google Scholar
  7. 7.
    Bryan, B., Eberhardt, F., Faloutsos, C.: Compact similarity joins. In: Proceedings of the IEEE International Conference on Data Engineering, ICDE 2008, pp. 346–355. IEEE (2008)Google Scholar
  8. 8.
    Samet, H.: Techniques for similarity searching in multimedia databases. PVLDB 3(2), 1649–1650 (2010)Google Scholar
  9. 9.
    Bustos, B., Navarro, G.: Improving the space cost of k-NN search in metric spaces by using distance estimators. Multimedia Tools and Appl. 41(2), 215–233 (2009)CrossRefGoogle Scholar
  10. 10.
    Berchtold, S., Böhm, C., Braunmüller, B., Keim, D.A., Kriegel, H.-P.: Fast parallel similarity search in multimedia databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 1–12. ACM (1997)Google Scholar
  11. 11.
    Alpkocak, A., Danisman, T., Ulker, T.: A Parallel Similarity Search in High Dimensional Metric Space Using M-Tree. In: Grigoras, D., Nicolau, A., Toursel, B., Folliot, B. (eds.) IWCC 2001. LNCS, vol. 2326, pp. 166–171. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  12. 12.
    Manjarrez-Sanchez, J., Martinez, J., Valduriez, P.: Efficient Processing of Nearest Neighbor Queries in Parallel Multimedia Databases. In: Bhowmick, S.S., Küng, J., Wagner, R. (eds.) DEXA 2008. LNCS, vol. 5181, pp. 326–339. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  13. 13.
    Jacox, E.H., Samet, H.: Spatial join techniques. ACM Transactions on Database Systems 32(1) (2007)Google Scholar
  14. 14.
    Wu, Z., Cao, Z., Wang, Y.: Multimedia selection operation placement. Multimedia Tools and Appl. 54(1), 69–96 (2011)CrossRefGoogle Scholar
  15. 15.
    Klampanos, I.A., Jose, J.M.: An Evaluation of a Cluster-Based Architecture for Peer-to-Peer Information Retrieval. In: Wagner, R., Revell, N., Pernul, G. (eds.) DEXA 2007. LNCS, vol. 4653, pp. 380–391. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  16. 16.
    Shen, H.T., Huang, Z., Cao, J., Zhou, X.: High-dimensional indexing with oriented cluster representation for multimedia databases. In: Proceedings of the IEEE International Conference on Multimedia and Expo, ICME 2009, pp. 1628–1631. IEEE (2009)Google Scholar
  17. 17.
    Hellerstein, J.M.: Generalized Search Tree. In: Encyclopedia of Database Systems, pp. 1222–1224. Springer, US (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Harald Kosch
    • 1
  • Andreas Wölfl
    • 1
  1. 1.Distributed Information Systems, Faculty of Informatics and MathematicsUniversity of PassauGermany

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