Scalable keyword search over relational data streams by aggressive candidate network consolidation
作者：
Highlights：
• The proposed keyword search method can efficiently deal with long queries with many keywords.
• It greatly outperforms the existing approaches and is more suitable for real search engine.
• The new query plan MX-structure maximizes shared processing among all intermediate results.
• MX-structure keeps all intermediate results together in the form of labeled graph.
• MX-structure tracks the match status of all intermediate results by using sub-spaces inside node buffers and can greatly improve query matching speed.
摘要
•The proposed keyword search method can efficiently deal with long queries with many keywords.•It greatly outperforms the existing approaches and is more suitable for real search engine.•The new query plan MX-structure maximizes shared processing among all intermediate results.•MX-structure keeps all intermediate results together in the form of labeled graph.•MX-structure tracks the match status of all intermediate results by using sub-spaces inside node buffers and can greatly improve query matching speed.
论文关键词：Keyword search,Relational streams,Candidate network
论文评审过程：Received 7 June 2018, Revised 30 October 2018, Accepted 19 December 2018, Available online 24 December 2018, Version of Record 31 December 2018.
论文官网地址：https://doi.org/10.1016/j.is.2018.12.004
