Assessing the behavior and performance of a supervised term-weighting technique for topic-based retrieval

作者：

Highlights：

• A supervised term-weighting scheme is extensively analyzed and evaluated.

• The scheme is evaluated in the task of query-term selection for topic-based retrieval.

• The performance comparison is carried out against eighteen methods on three data sets with promising results.

• A full manually labeled data set and the full code is made publicly available.

摘要

•A supervised term-weighting scheme is extensively analyzed and evaluated.•The scheme is evaluated in the task of query-term selection for topic-based retrieval.•The performance comparison is carried out against eighteen methods on three data sets with promising results.•A full manually labeled data set and the full code is made publicly available.

论文关键词：Term weighting,Variable extraction,Information retrieval,Query-term selection,Topic-based retrieval

论文评审过程：Received 16 July 2020, Revised 27 November 2020, Accepted 21 December 2020, Available online 5 February 2021, Version of Record 5 February 2021.

论文官网地址：https://doi.org/10.1016/j.ipm.2020.102483