Efficient k-nearest neighbor search based on clustering and adaptive k values

作者：

Highlights：

• Efficient kNN search based on feature learning, clustering, and adaptive k values.

• Several proposals to automatically optimize the search parameters.

• Comprehensive experimentation with 10 datasets of different typology and size.

• Results demonstrate that the proposal outperforms state-of-the-art methods.

摘要

•Efficient kNN search based on feature learning, clustering, and adaptive k values.•Several proposals to automatically optimize the search parameters.•Comprehensive experimentation with 10 datasets of different typology and size.•Results demonstrate that the proposal outperforms state-of-the-art methods.

论文关键词：k-Nearest Neighbor,Efficient search,Clustering,Feature learning

论文评审过程：Received 6 March 2021, Revised 21 August 2021, Accepted 27 September 2021, Available online 28 September 2021, Version of Record 3 October 2021.

论文官网地址：https://doi.org/10.1016/j.patcog.2021.108356