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English Information

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Authors
# Name
1 Larissa Shimomura(l.capobianco.shimomura@tue.nl)
2 Daniel Kaster(dskaster@uel.br)

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Reference
# Reference
1 Amagata, D., Onizuka, M., and Hara, T. (2022). Fast, exact, and parallel-friendly outlier detection algorithms with proximity graph in metric spaces. The VLDB Journal, pages 1–25.
2 Fu, C., Xiang, C., Wang, C., and Cai, D. (2019). Fast approximate nearest neighbor search with the navigating spreading-out graph. Proc. VLDB Endow., 12(5):461–474.
3 Hajebi, K., Abbasi-Yadkori, Y., Shahbazi, H., and Zhang, H. (2011). Fast approximate nearest-neighbor search with k-nearest neighbor graph. In Int’l Joint Conf. on Artificial Intelligence IJCAI, pages 1312–1317.
4 Malkov, Y. A. and Yashunin, D. A. (2020). Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(4):824–836.
5 Navarro, G. (2002). Searching in metric spaces by spatial approximation. The VLDB Journal The Int’l Journal on Very Large Data Bases, 11(1):28–46.
6 Oyamada, R. S., Shimomura, L. C., Junior, S. B., and Kaster, D. S. (2020). Towards proximity graph auto-configuration: An approach based on meta-learning. In Darmont, J., Novikov, B., and Wrembel, R., editors, Advances in Databases and Information Systems, pages 93–107, Cham. Springer International Publishing.
7 Paredes, R., Chávez, E., Figueroa, K., and Navarro, G. (2006). Practical Construction of k-Nearest Neighbor Graphs in Metric Spaces, pages 85–97. Springer Berlin Heidelberg.
8 Shimomura, L. C., Oyamada, R. S., Vieira, M. R., and Kaster, D. S. (2021). A survey on graph-based methods for similarity searches in metric spaces. Information Systems, 95:101507.
9 Wang, M., Xu, X., Yue, Q., and Wang, Y. (2021). A comprehensive survey and experimental comparison of graph-based approximate nearest neighbor search. Proc. VLDB Endow., 14(11):1964–1978.
10 Zezula, P., Amato, G., Dohnal, V., and Batko, M. (2010). Similarity Search: The Metric Space Approach. Springer, 1st edition.