Exploratory product search using top-k join queries
作者：
Highlights：
• We propose a new exploration technique using eXploratory Top-k Join (XTJ) queries.
• We analyze the XTJ-query properties and we propose an efficient algorithm (XRJN).
• We provide strong theoretical guarantees on the performance of our algorithm.
• We introduce an improved pulling strategy that reduces the overall processing cost.
• We generalize XTJ queries to efficiently combinations organized in groups and to include various aggregation functions.
摘要
Highlights•We propose a new exploration technique using eXploratory Top-k Join (XTJ) queries.•We analyze the XTJ-query properties and we propose an efficient algorithm (XRJN).•We provide strong theoretical guarantees on the performance of our algorithm.•We introduce an improved pulling strategy that reduces the overall processing cost.•We generalize XTJ queries to efficiently combinations organized in groups and to include various aggregation functions.
论文关键词：Exploratory search,Top-k queries,Join queries,Product combinations,Combination ranking
论文评审过程：Received 21 April 2015, Revised 30 June 2016, Accepted 3 September 2016, Available online 16 September 2016, Version of Record 28 October 2016.
论文官网地址：https://doi.org/10.1016/j.is.2016.09.004
