Abstract
With the emerging applications dealing with complex multimedia retrieval, such as the multimedia exploration, appropriate indexing structures need to be designed. A formalism for compact metric region description can significantly simplify the design of algorithms for such indexes, thus more complex and efficient metric indexes can be developed. In this paper, we introduce the cut-regions that are suitable for compact metric region description and we discuss their basic operations. To demonstrate the power of cut-regions, we redefine the PM-Tree using the cut-region formalism and, moreover, we use the formalism to describe our new improvements of the PM-Tree construction techniques. We have experimentally evaluated that the improved construction techniques lead to query performance originally obtained just using expensive construction techniques. Also in comparison with other metric and spatial access methods, the revisited PM-Tree proved its benefits.
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References
Beecks, C., Lokoč, J., Seidl, T., Skopal, T.: Indexing the signature quadratic form distance for efficient content-based multimedia retrieval. In: Proc. ACM International Conference on Multimedia Retrieval (2011)
Beecks, C., Skopal, T., Schoeffmann, K., Seidl, T.: Towards large-scale multimedia exploration. In: Das, G., Hsristidis, V., Ilyas, I. (eds.) Proceedings of the 5th International Workshop on Ranking in Databases (DBRank 2011), pp. 31–33. VLDB, Seattle, WA, USA (2011)
Bolettieri, P., Esuli, A., Falchi, F., Lucchese, C., Perego, R., Piccioli, T., Rabitti, F.: CoPhIR: a test collection for content-based image retrieval. CoRR, abs/0905.4627v2 (2009)
Chávez, E., Navarro, G., Baeza-Yates, R., Marroquín, J.L.: Searching in metric spaces. ACM Computing Surveys 33(3), 273–321 (2001)
Gonzalez, E.C., Figueroa, K., Navarro, G.: Effective proximity retrieval by ordering permutations. IEEE Trans. Pattern Anal. Mach. Intell. 30(9), 1647–1658 (2008)
Ciaccia, P., Patella, M., Zezula, P.: M-tree: An Efficient Access Method for Similarity Search in Metric Spaces. In: VLDB 1997, pp. 426–435 (1997)
Geusebroek, J.-M., Burghouts, G.J., Smeulders, A.W.M.: The Amsterdam Library of Object Images. International Journal of Computer Vision 61(1), 103–112 (2005)
Hetland, M.L.: The Basic Principles of Metric Indexing. In: Coello, C.A.C., Dehuri, S., Ghosh, S. (eds.) Swarm Intelligence for Multi-objective Problems in Data Mining. SCI, vol. 242, pp. 199–232. Springer, Heidelberg (2009)
Hettich, S., Bay, S.D.: The UCI KDD archive (1999), http://kdd.ics.uci.edu
Jakub, L., Tomáš, S.: On Reinsertions in M-tree. In: SISAP 2008: Proceedings of the First International Workshop on Similarity Search and Applications (SISAP 2008), pp. 121–128. IEEE Computer Society, Washington, DC (2008)
Mico, M.L., Oncina, J., Vidal, E.: A new version of the nearest-neighbour approximating and eliminating search algorithm (aesa) with linear preprocessing time and memory requirements. Pattern Recogn. Lett. 15(1), 9–17 (1994)
Novak, D., Batko, M., Zezula, P.: Metric index: An efficient and scalable solution for precise and approximate similarity search. Inf. Syst. 36(4), 721–733 (2011)
Samet, H.: Foundations of Multidimensional and Metric Data Structures. Morgan Kaufmann (2006)
Skopal, T.: Pivoting M-tree: A Metric Access Method for Efficient Similarity Search. In: Proceedings of the 4th Annual Workshop DATESO, Desná, Czech Republic, pp. 21–31 (2004) ISBN 80-248-0457-3; also available at CEUR, vol. 98, ISSN 1613-0073, http://www.ceur-ws.org/Vol-98
Skopal, T.: Unified framework for fast exact and approximate search in dissimilarity spaces. ACM Transactions on Database Systems 32(4), 1–46 (2007)
Skopal, T., Lokoč, J.: New Dynamic Construction Techniques for M-tree. Journal of Discrete Algorithms 7(1), 62–77 (2009)
Skopal, T., Lokoč, J.: Answering Metric Skyline Queries by PM-tree. In: Proceedings of the Dateso 2010 Workshop, vol. 567, pp. 22–37. Matfyz Press (2010)
Skopal, T., Pokorný, J., Snášel, V.: Nearest Neighbours Search Using the PM-Tree. In: Zhou, L.-z., Ooi, B.-C., Meng, X. (eds.) DASFAA 2005. LNCS, vol. 3453, pp. 803–815. Springer, Heidelberg (2005)
Zezula, P., Amato, G., Dohnal, V., Batko, M.: Similarity Search: The Metric Space Approach. Springer (2005)
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Lokoč, J., Čech, P., Novák, J., Skopal, T. (2012). Cut-Region: A Compact Building Block for Hierarchical Metric Indexing. In: Navarro, G., Pestov, V. (eds) Similarity Search and Applications. SISAP 2012. Lecture Notes in Computer Science, vol 7404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32153-5_7
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DOI: https://doi.org/10.1007/978-3-642-32153-5_7
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