The role of local dimensionality measures in benchmarking nearest neighbor search
作者：
Highlights：
• Local dimensionality measures allow to build query sets of different degrees of difficulty.
• Local Intrinsic Dimensionality is the most effective at selecting queries.
• Using average performance measures hides interesting behavior of algorithms.
• Datasets commonly used as benchmarks are not diverse enough.
摘要
•Local dimensionality measures allow to build query sets of different degrees of difficulty.•Local Intrinsic Dimensionality is the most effective at selecting queries.•Using average performance measures hides interesting behavior of algorithms.•Datasets commonly used as benchmarks are not diverse enough.
论文关键词：Nearest neighbor search,Benchmarking
论文评审过程：Received 14 March 2020, Revised 4 January 2021, Accepted 17 May 2021, Available online 25 May 2021, Version of Record 5 June 2021.
论文官网地址：https://doi.org/10.1016/j.is.2021.101807
