The Merkurion approach for similarity searching optimization in Database Management Systems
作者：
Highlights：
• A similarity-based extension for DBMS's query optimizers is proposed.
• Both logical and physical optimization of similarity queries are addressed.
• Some similarity-based synopses are more suitable than others for logical/physical optimizations.
• Boosted k-nearest neighbors algorithms may outperform the incremental approach.
摘要
Highlights•A similarity-based extension for DBMS's query optimizers is proposed.•Both logical and physical optimization of similarity queries are addressed.•Some similarity-based synopses are more suitable than others for logical/physical optimizations.•Boosted k-nearest neighbors algorithms may outperform the incremental approach.
论文关键词：Similarity searching,Query optimization,Selectivity estimation,Design and implementation techniques
论文评审过程：Received 29 September 2016, Revised 3 August 2017, Accepted 18 September 2017, Available online 23 September 2017, Version of Record 5 February 2018.
论文官网地址：https://doi.org/10.1016/j.datak.2017.09.003
