BOLDSC: A New Dynamic, Secondary-Memory Metric Index
Fecha
2025-10-01
Nota de Acceso
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ISSN de la revista
Título del volumen
Editor
Springer Nature
ISBN
9783032007179
ISSN
ISSNe
9783032007186
Resumen
Metric space searching addresses the problem of efficient similarity searching across diverse applications, in particular for non-structured objects, for instance, natural language or images. Although promising, this approach is still immature in several aspects that are well-established in traditional databases. Particularly, most indexing schemes are not dynamic, as they cannot efficiently handle insertions over an ongoing index without significant performance degradation. Moreover, very few of them work efficiently in secondary memory. The List of Clusters (LC) has proven to be a competitive index in main memory due to its simplicity and good search performance in high dimensional metric spaces. We introduce a new dynamic, secondary-memory LC variant. Our new index efficiently handles the secondary memory scenario and achieves competitive search and insertion times compared to the state-of-the-art, making it a practical alternative for large-scale database applications. Also, our ideas are applicable to other secondary-memory indexes, where it is possible to control the disk page occupation.
Descripción
Lugar de Publicación
Cham, Suiza
Sponsorship
Citación
En: Patricia Pesado, Pablo Thomas (eds.). Computer Science – CACIC 2024. CACIC 2024. Communications in Computer and Information Science, vol 2520. Springer, Cham, 2026. pp.133--148.
Palabras clave
Metric space searching, Secondary memory index
Licencia
Atribución-NoComercial-CompartirIgual 3.0 Chile (CC BY-NC-SA 3.0 CL)