MIGUE-Sim: Speeding Up Similarity Queries with Native RDBMS Resources-Reference-Cited by-同舟云学术

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MIGUE-Sim: Speeding Up Similarity Queries with Native RDBMS Resources

Published:2024-04-08 Issue: Volume:5 Page:321-328
ISSN:
Container-title:Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing
language:
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Author:

Eleuterio Igor¹^ORCID,Cazzolato Mirela¹²^ORCID,Teixeira Larissa Roberta¹^ORCID,Gutierrez Marco Antonio²^ORCID,Traina Agma Juci Machado¹^ORCID,Traina Caetano¹^ORCID

Affiliation:

1. Institute of Mathematics and Computer Science (ICMC), University of Sao Paulo, São Carlos, Brazil

2. The Heart Institute (InCor), University of Sao Paulo, São Paulo, Brazil

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES)

São Paulo Research Foundation (FAPESP)

National Council for Scientific and Technological Development (CNPq)

JIT Education

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3605098.3636019

Reference25 articles.

1. Leonidas Akritidis and Panayiotis Bozanis. 2023. Low-Dimensional Text Representations for Sentiment Analysis NLP Tasks. SN Computer Science 4, 474 (2023).

3. MUFIN: A Multi-feature Indexing Network

4. Michal Batko, David Novak, and Pavel Zezula. 2007. MESSIF: Metric Similarity Search Implementation Framework. In Digital Libraries: Research and Development, Costantino Thanos, Francesca Borri, and Leonardo Candela (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 1--10.

5. Seamless Integration of Distance Functions and Feature Vectors for Similarity-Queries Processing;Naves Bedo Marcos Vinicius;Journal of Information and Data Management,2014

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