On the average performance of orthogonal range search in multidimensional data structures
In this work we present the average-case analysis of orthogonal range search for several multidimensional data structures. We first consider random relaxed K-d trees as a prototypical example and later extend our results to several different multidimensional data structures. We show that the perform...
| Autores: | , |
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| Tipo de recurso: | informe técnico |
| Fecha de publicación: | 2001 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/97828 |
| Acceso en línea: | https://hdl.handle.net/2117/97828 |
| Access Level: | acceso abierto |
| Palabra clave: | Orthogonal range search Multidimensional data structures Random relaxed K-d trees Àrees temàtiques de la UPC::Informàtica |
| Sumario: | In this work we present the average-case analysis of orthogonal range search for several multidimensional data structures. We first consider random relaxed K-d trees as a prototypical example and later extend our results to several different multidimensional data structures. We show that the performance of range searches is related to the performance of a variant of partial matches which simplifies the analysis and provides a tight asymptotic estimate for the expected cost of range searches. |
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