MEANS: A medical question-answering system combining NLP techniques and semantic Web technologies
作者：
Highlights：
• We propose a semantic question answering system (MEANS) for the medical domain.
• We introduce a novel query relaxation approach for question answering.
• MEANS integrates NLP methods allowing a deep analysis of questions and documents.
• MEANS uses semantic Web technologies and standards for data sharing and integration.
• Our experiments show promising results in terms of MRR and precision.
摘要
•We propose a semantic question answering system (MEANS) for the medical domain.•We introduce a novel query relaxation approach for question answering.•MEANS integrates NLP methods allowing a deep analysis of questions and documents.•MEANS uses semantic Web technologies and standards for data sharing and integration.•Our experiments show promising results in terms of MRR and precision.
论文关键词：Question answering,Natural language processing,Semantic search,Medical informatics
论文评审过程：Received 15 August 2014, Revised 16 April 2015, Accepted 22 April 2015, Available online 11 June 2015, Version of Record 11 June 2015.
论文官网地址：https://doi.org/10.1016/j.ipm.2015.04.006
