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SISAP 2023 Indexing Challenge – Learned Metric Index

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SLANINÁKOVÁ Terézia PROCHÁZKA David ANTOL Matej OĽHA Jaroslav DOHNAL Vlastislav

Rok publikování 2023
Druh Článek ve sborníku
Konference Similarity Search and Applications. SISAP 2023. Lecture Notes in Computer Science, vol 14289
Fakulta / Pracoviště MU

Fakulta informatiky

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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