Dynamic similarity search in multi-metric spaces

Proceedings of the ACM International Multimedia Conference and Exhibition

Volumn , Issue , 2006, Pages 137-146

  Bustos, Benjamin ^a   Skopal, Tomáš ^b  

^a UNIVERSITY OF KONSTANZ   (Germany)

^b CHARLES UNIVERSITY   (Czech Republic)

Author keywords

Combination of metric functions; Content based indexing and retrieval; Nearest neighbor queries

Indexed keywords

DATABASE SYSTEMS; DECISION TREES; FUNCTION EVALUATION; MULTIMEDIA SYSTEMS; QUERY PROCESSING;

CONTENT-BASED INDEXING; METRIC FUNCTIONS; MULTI-MEDIA DATABASES; NEAREST NEIGHBOR QUERIES;

CONTENT BASED RETRIEVAL;

EID: 34547398447     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1178677.1178698     Document Type: Conference Paper

References (15)

1. C. Böhm, S. Berchtold, and D. Keim. Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases. ACM Computing Surveys, 33(3):322-373, 2001.
2. B. Bustos, D. Keim, D. Saupe, T. Schreck, and D. Vranić. Automatic selection and combination of descriptors for effective 3D similarity search. In Proc. IEEE International Workshop on Multimedia Content-based Analysis and Retrieval (MCBAB'04), pages 514-521. IEEE Computer Society, 2004.
3. B. Bustos, D. Keim, D. Saupe, T. Schreck, and D. Vranić. Using entropy impurity for improved 3D object similarity search. In Proc. IEEE International Conference on Multimedia and Expo (ICME'04), pages 1303-1306. IEEE, 2004.
4. B. Bustos, D. Keim, D. Saupe, T. Schreck, and D. Vranić. An experimental effectiveness comparison of methods for 3D similarity search. Intl. Journal on Digital Libraries, 6(1):39-54, 2006.
5. B. Bustos, D. Keim, and T. Schreck. A pivot-based index structure for combination of feature vectors. In Proc. 20th Annual ACM Symposium on Applied Computing, Multimedia and Visualization Track (SAC-MV05), pages 1180-1184. ACM Press, 2005.
6. E. Chavez, G. Navarro, R. Baeza-Yates, and J. Marroquin. Searching in metric spaces. ACM Computing Surveys, 33(3):273-321, 2001.
7. P. Ciaccia and M. Patella. Searching in metric spaces with user-defined and approximate distances. ACM Transactions on Database Systems, 27(4):398-437, 2002.
8. P. Ciaccia, M. Patella, and P. Zezula. M-tree: An efficient access method for similarity search in metric spaces. In Proc. 23rd Conference on Very Large Databases (VLDB'97), pages 426-435. Morgan Kaufmann, 1997.
9. A. de Vries, N. Mamoulis, N. Nes, and M. Kersten. Efficient k-NN search on vertically decomposed data. In Proc. ACM International Conference on Management of Data (SIGMOD'02), pages 322-333. ACM Press, 2002.
10. S. Hettich and S. Bay. The UCI KDD archive [http://kdd.ics.uci.edu], 1999.
11. D. Keim. Efficient geometry-based similarity search of 3D spatial databases. In Proc. ACM International Conference on Management of Data (SIGMOD'99), pages 419-430. ACM Press, 1999.
12. T. Skopal. On fast non-metric similarity search by metric access methods. In Proc. 10th International Conference on Extending Database Technology (EDBT06), LNCS 3896, pages 718-736. Springer, 2006.
13. T. Skopal, J. Pokorný, M. Krátký, and V. Snášel. Revisiting M-tree building principles. In Proc. 7th East European Conference on Advances in Databases and Information Systems (ADBIS'03), LNCS 2798, pages 148-162. Springer, 2003.
14. T. Skopal, J. Pokorný, and V. Snášel. Nearest neighbours search using the PM-tree. In Proc. 10th International Conference on Database Systems for Advanced Applications (DASFAA '05), LNCS 3453, pages 803-815. Springer, 2005.
15. P. Zezula, G. Amato, V. Dohnal, and M. Batko. Similarity Search: The Metric Space Approach (Advances in Database Systems). Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2005.