Information retrieval from scientific abstract and citation databases: A query-by-documents approach based on Monte-Carlo sampling

作者：

Highlights：

• Presentation of novel query-by-document approach.

• Incorporation of statistical Monte-Carlo sampling method in query construction step.

• Document (appearance) frequency is used as method inherent relevance ranking metric.

• Comparison of methodology with sequential sampling and expert string construction.

• High seed recall in retrieved corpora.

摘要

•Presentation of novel query-by-document approach.•Incorporation of statistical Monte-Carlo sampling method in query construction step.•Document (appearance) frequency is used as method inherent relevance ranking metric.•Comparison of methodology with sequential sampling and expert string construction.•High seed recall in retrieved corpora.

论文关键词：Systematic literature review,Decision-making support,Recommender system,Monte-Carlo sampling,Knowledge management

论文评审过程：Received 10 May 2021, Revised 13 January 2022, Accepted 20 March 2022, Available online 29 March 2022, Version of Record 11 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116967