APOTHEOSIS: An efficient approximate similarity search system
APOTHEOSIS is a tool for efficiently identifying and comparing data similarity in large datasets, addressing challenges faced by traditional methods such as scalability and speed. APOTHEOSIS overcomes them by combining advanced algorithms and data structures, enabling fast and accurate similarity analysis. Specifically, it uses a custom hierarchical small navigation world as an approximate K -nearest neighbors search method, and approximate similarity digests algorithms to find common features between similar data items, also supporting various distance metrics beyond vector-based approaches. Our software tool is designed for seamless integration into research workflows, improving reproducibility and facilitating the comparison of large-scale, high-dimensional data comparison across multiple domains.
Authors
- Eduardo Mena (ORCID: https://orcid.org/0000-0002-7462-0080)
- Ricardo J. Rodríguez (ORCID: https://orcid.org/0000-0001-7982-0359)
- Daniel Huici
Institutions
- Universidad de Zaragoza (ES)
Publication Details
- Journal
- SoftwareX
- Published
- 2024-12-24
- DOI
- https://doi.org/10.1016/j.softx.2024.102016
- Citations
- 1
- Primary Topic
- Algorithms and Data Compression
- Type
- article
- Field-Weighted Citation Impact
- 0.35
Funders
- European Commission
- Instituto Nacional de Ciberseguridad
- Agencia Estatal de Investigación