Semantic and explainable research-related recommendation system based on semi-supervised methodology using BERT and LDA models

作者：

Highlights：

• We propose a novel research-related recommendation system using BERT and LDA.

• We propose an explainable keywords extractor using BERT's self-attention mechanism.

• Our method provides an effective research-related information retrieval process.

摘要

•We propose a novel research-related recommendation system using BERT and LDA.•We propose an explainable keywords extractor using BERT's self-attention mechanism.•Our method provides an effective research-related information retrieval process.

论文关键词：Recommendation system,Semi-supervised learning,BERT,Explainable deep-learning

论文评审过程：Received 29 August 2020, Revised 28 March 2021, Accepted 6 November 2021, Available online 14 November 2021, Version of Record 18 November 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116209