Abstract
This paper proposes to transform data scanned randomly in a well-defined space (e.g, Euclidean) along a hierarchical irregular pyramidal structure in an attempt reduce search time consumed querying these random data. Such a structure is built as a series of graphs with different resolutions. Levels are constructed and surviving cells are chosen following irregular irregular pyramidal rules and according to a proximity criterion among the space points under consideration. Experimental results show that using such a structure to query data can save considerable search time.
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Elias, R., Al Ashraf, M., Aly, O. (2009). From Random to Hierarchical Data through an Irregular Pyramidal Structure. In: Torsello, A., Escolano, F., Brun, L. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2009. Lecture Notes in Computer Science, vol 5534. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02124-4_33
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DOI: https://doi.org/10.1007/978-3-642-02124-4_33
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