Abstract
Indexing is the most effective technique to speed up queries in databases. While traditional indexing approaches are used for exact search, a query object may not be always identical to an existing data object in similarity search. This paper proposes a new dynamic data structure called Hypherspherical Region Graph (HRG) to efficiently index a large volume of data objects as a graph for similarity search in metric spaces. HRG encodes the given dataset in a smaller number of vertices than the known graph index, Incremental-RNG, while providing flexible traversal without incurring backtracking as observed in tree-based indices. An empirical analysis performed on search time shows that HRG outperforms Incremental-RNG in both cases. HRG, however, outperforms tree-based indices in range search only when the data dimensionality is not so high.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ciaccia, P., Patella, M., Zezula, P.: M-tree: An efficient access method for similarity search in metric spaces. In: Proceedings of the 23rd International Conference on Very Large Data Bases, San Francisco, CA, USA, pp. 426–435 (1997)
Traina, C., Traina, A., Seeger, B., Faloutsos, C.: Slim-trees: High performance metric trees minimizing overlap between nodes. In: Zaniolo, C., Grust, T., Scholl, M.H., Lockemann, P.C. (eds.) EDBT 2000. LNCS, vol. 1777, pp. 51–65. Springer, Heidelberg (2000)
Vieira, M.R., Traina Jr., C., Chino, F.J.T., Traina, A.J.M.: Dbm-tree: A dynamic metric access method sensitive to local density data. In: Brazilian Symposium on Databases, pp. 163–177 (2004)
Navarro, G.: Searching in metric spaces by spatial approximation. The VLDB Journal 11(1), 28–46 (2002)
Hacid, H., Yoshida, T.: Incremental neighborhood graphs construction for multidimensional databases indexing. In: Advances in Artificial Intelligence, pp. 405–416 (2007)
Hacid, H., Zighed, A.D.: An effective method for locally neighborhood graphs updating. In: Database and Expert Systems Applications, pp. 930–939 (2005)
Zhao, D., Yang, L.: Incremental construction of neighborhood graphs for nonlinear dimensionality reduction. In: Proceedings of the 18th International Conference on Pattern Recognition, pp. 177–180 (2006)
Lee, C., Kim, D., Shin, H., Kim, D.-S.: Efficient computation of elliptic gabriel graph. In: International Conference on Computational Science and Applications, pp. 440–448 (2006)
Jaromczyk, J., Toussaint, G.: Relative neighborhood graphs and their relatives. In: Proceedings of IEEE, vol. 80, pp. 1502–1517 (1992)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Florez, O.U., Lim, S. (2008). HRG: A Graph Structure for Fast Similarity Search in Metric Spaces. In: Bhowmick, S.S., Küng, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2008. Lecture Notes in Computer Science, vol 5181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85654-2_7
Download citation
DOI: https://doi.org/10.1007/978-3-540-85654-2_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85653-5
Online ISBN: 978-3-540-85654-2
eBook Packages: Computer ScienceComputer Science (R0)