SISAP 2023 Indexing Challenge – Learned Metric Index
| Autoři | |
|---|---|
| Rok publikování | 2023 |
| Druh | Článek ve sborníku |
| Konference | Similarity Search and Applications. SISAP 2023. Lecture Notes in Computer Science, vol 14289 |
| Fakulta / Pracoviště MU | |
| Citace | |
| Doi | http://dx.doi.org/10.1007/978-3-031-46994-7_24 |
| Klíčová slova | sisap indexing challenge; learned metric index; similarity search; machine learning for indexing; performance benchmarking |
| Popis | This submission into the SISAP Indexing Challenge examines the experimental setup and performance of the Learned Metric Index, which uses an architecture of interconnected learned models to answer similarity queries. An inherent part of this design is a great deal of flexibility in the implementation, such as the choice of particular machine learning models, or their arrangement in the overall architecture of the index. Therefore, for the sake of transparency and reproducibility, this report thoroughly describes the details of the specific Learned Metric Index implementation used to tackle the challenge. |
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