Abstract
Proximity searching can be formulated as an optimization problem, being the goal function to find the object minimizing the distance to a given query by traversing a graph with a greedy algorithm. This formulation can be traced back to early formulations defined for vector spaces, and other recent approaches defined for the more general setup of metric spaces.
In this paper we introduce three searching algorithms generalizing to local search other than greedy, and experimentally prove that our approach improves significantly the state of the art. In particular, our contributions have excellent trade-offs among speed, recall and memory usage; making our algorithms suitable for real world applications. As a byproduct, we present an open source implementation of most of the near neighbor search algorithms in the literature.
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References
Silpa-Anan, C., Hartley, R.: Optimised kd-trees for fast image descriptor matching. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1–8, June 2008
Arya, S., Mount, D.M.: Approximate nearest neighbor queries in fixed dimensions. In: Proceedings of the Fourth Annual ACM/SIGACT-SIAM Symposium on Discrete Algorithms, pp. 271–280, Austin, Texas, 25–27 January 1993 (1993)
Houle, M.E., Nett, M.: Rank cover trees for nearest neighbor search. In: Brisaboa, N., Pedreira, O., Zezula, P. (eds.) SISAP 2013. LNCS, vol. 8199, pp. 16–29. Springer, Heidelberg (2013)
Malkov, Y., Ponomarenko, A., Logvinov, A., Krylov, V.: Scalable distributed algorithm for approximate nearest neighbor search problem in high dimensional general metric spaces. In: Navarro, G., Pestov, V. (eds.) SISAP 2012. LNCS, vol. 7404, pp. 132–147. Springer, Heidelberg (2012)
Malkov, Y., Ponomarenko, A., Logvinov, A., Krylov, V.: Approximate nearest neighbor algorithm based on navigable small world graphs. Information Systems 45, 61–68 (2014)
Chávez, E., Graff, M., Navarro, G., Téllez, E.: Near neighbor searching with K nearest references. Information Systems 51, 43–61 (2015)
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Ruiz, G., Chávez, E., Graff, M., Téllez, E.S. (2015). Finding Near Neighbors Through Local Search. In: Amato, G., Connor, R., Falchi, F., Gennaro, C. (eds) Similarity Search and Applications. SISAP 2015. Lecture Notes in Computer Science(), vol 9371. Springer, Cham. https://doi.org/10.1007/978-3-319-25087-8_10
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DOI: https://doi.org/10.1007/978-3-319-25087-8_10
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