Natural language based analysis of SQuAD: An analytical approach for BERT
作者：
Highlights：
• The NLP-based Question Answering System (NLP-QAS) is proposed for answer detection.
• Remove and compare, Search with NER and POS (RNP) methods has been developed.
• It’s the first one that extends the BERT model’s capability with RNP methods.
• The accuracy of BERT has increased by approximately 1.1% to 2.4% with RNP methods.
• It is proved that BERT models don’t use NLP-based techniques sufficiently.
摘要
•The NLP-based Question Answering System (NLP-QAS) is proposed for answer detection.•Remove and compare, Search with NER and POS (RNP) methods has been developed.•It’s the first one that extends the BERT model’s capability with RNP methods.•The accuracy of BERT has increased by approximately 1.1% to 2.4% with RNP methods.•It is proved that BERT models don’t use NLP-based techniques sufficiently.
论文关键词：Natural language processing,BERT,Text analysis,Question answering,SQuAD
论文评审过程：Received 7 June 2021, Revised 18 September 2021, Accepted 19 January 2022, Available online 31 January 2022, Version of Record 7 February 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.116592
