A new dynamic, secondary-memory metric index
Metric space searching addresses the problem of efficient similarity searching in many applications. Although promising, the metric space approach is still immature in several aspects that are well established in traditional databases. Particularly, most indexing schemes are not dynamic, that is, fe...
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| Autores principales: | , , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/176400 |
| Aporte de: |
| Sumario: | Metric space searching addresses the problem of efficient similarity searching in many applications. Although promising, the metric space approach is still immature in several aspects that are well established in traditional databases. Particularly, most indexing schemes are not dynamic, that is, few of them tolerate insertion of elements at reasonable cost over an existing index with none or mild performance degrading; and even less of them work efficiently in secondary memory. The List of Clusters (LC) is a competitive index in main memory. We introduce a new dynamic, secondary-memory variant of the LC. Our new index handles well the secondary memory scenario and is competitive with the state of the art, becoming a useful alternative in a wide range of database applications. Also, our ideas are applicable to other secondary-memory indexes, where it is possible to control the disk page occupation. |
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