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English Information

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Authors
# Name
1 Daniel Kaster(dskaster@uel.br)
2 Matheus Bastos(mathheusb@gmail.com)

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Reference
# Reference
1 Antol, M., Ol’ha, J., Slanináková, T., and Dohnal, V. (2021). Learned metric index - proposition of learned indexing for unstructured data. Information Systems, 100:101774.
2 Bolettieri, P., Esuli, A., Falchi, F., Lucchese, C., Perego, R., Piccioli, T., and Rabitti, F. (2009). CoPhIR: a test collection for content-based image retrieval. arXiv preprint arXiv:0905.4627.
3 Boytsov, L. and Naidan, B. (2013). Engineering efficient and effective non-metric space library. In International Conference on Similarity Search and Applications, pages 280-293. Springer.
4 Cutler, A., Cutler, D. R., and Stevens, J. R. (2012). Random forests. In Ensemble machine learning, pages 157-175. Springer.
5 Hajebi, K., Abbasi-Yadkori, Y., Shahbazi, H., and Zhang, H. (2011). Fast approximate nearest-neighbor search with k-nearest neighbor graph. In Twenty-Second International Joint Conference on Artificial Intelligence.
6 Kraska, T., Beutel, A., Chi, E. H., Dean, J., and Polyzotis, N. (2018). The case for learned index structures. In Proceedings of the 2018 International Conference on Management of Data, pages 489-504.
7 Navarro, G. (2002). Searching in metric spaces by spatial approximation. The VLDB Journal, 11(1):28-46.
8 Novak, D., Batko, M., and Zezula, P. (2011). Metric index: An efficient and scalable solution for precise and approximate similarity search. Information Systems, 36(4):721-733.
9 Ocsa, A., Bedregal, C., and Cuadros-Vargas, E. (2007). A new approach for similarity queries using neighborhood graphs. In SBBD, pages 131-142.
10 Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., et al. (2011). Scikit-learn: Machine learning in python. the Journal of machine Learning research, 12:2825-2830.
11 Shimomura, L. C. and Kaster, D. S. (2019). Hgraph: a connected-partition approach to proximity graphs for similarity search. In International Conference on Database and Expert Systems Applications, pages 106-121. Springer.