ADOPS: Aspect Discovery OPinion Summarisation Methodology based on deep learning and subgroup discovery for generating explainable opinion summaries
作者：
Highlights：
• We present a novel methodology for aspect-based opinion summarisation.
• Our methodology combines deep learning and subgroup discovery methods.
• We categorise the aspects of restaurant reviews and classify their opinion values.
• The summaries are presented in explainable terms for humans as interesting rules.
• We release a new dataset for assessing opinion summarisation models.
摘要
•We present a novel methodology for aspect-based opinion summarisation.•Our methodology combines deep learning and subgroup discovery methods.•We categorise the aspects of restaurant reviews and classify their opinion values.•The summaries are presented in explainable terms for humans as interesting rules.•We release a new dataset for assessing opinion summarisation models.
论文关键词：Opinion summarisation,Deep learning,Aspect extraction,Subgroup discovery,Interesting rules
论文评审过程：Received 8 November 2020, Revised 21 July 2021, Accepted 29 August 2021, Available online 1 September 2021, Version of Record 9 September 2021.
论文官网地址：https://doi.org/10.1016/j.knosys.2021.107455
