Journal of Shanghai Jiao Tong University (Science) ›› 2018, Vol. 23 ›› Issue (5): 678-683.doi: 10.1007/s12204-018-1982-1

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A Chinese Question Answering System in Medical Domain

FENG Guofei (冯郭飞), DU Zhikang (杜智康), WU Xing (武星)   

  1. (a. School of Computer Engineering and Science; b. Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai 200444, China)
  • 出版日期:2018-10-01 发布日期:2018-10-07
  • 通讯作者: WU Xing (武星) E-mail:xingwu@shu.edu.cn

A Chinese Question Answering System in Medical Domain

FENG Guofei (冯郭飞), DU Zhikang (杜智康), WU Xing (武星)   

  1. (a. School of Computer Engineering and Science; b. Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai 200444, China)
  • Online:2018-10-01 Published:2018-10-07
  • Contact: WU Xing (武星) E-mail:xingwu@shu.edu.cn

摘要: Question answering systems offer a friendly interface for human beings to interact with massive online information. It is time consuming for users to retrieve useful medical information with search engines among massive online websites. An effort is made to build a Chinese Question Answering System in Medical Domain (CQASMD) to provide useful medical information for users. A large medical knowledge base with more than 300 thousand medical terms and their descriptions is firstly constructed to store the structured medical knowledge data, and classified with the FastText model. Furthermore, a Word2Vec model is adopted to capture the semantic meanings of words, and the questions and answers are processed with sentence embedding to capture semantic context information. Users’ questions are firstly classified and processed into a sentence vector and a matching algorithm is adopted to match the most similar question. After querying the constructed medical knowledge base, the corresponding answers to previous questions are responded to users. The architecture and flowchart of CQASMD is proposed, which will play an important role in self disease diagnosis and treatment.

关键词: question answering, knowledge base, FastText, sentence embedding, disease diagnosis

Abstract: Question answering systems offer a friendly interface for human beings to interact with massive online information. It is time consuming for users to retrieve useful medical information with search engines among massive online websites. An effort is made to build a Chinese Question Answering System in Medical Domain (CQASMD) to provide useful medical information for users. A large medical knowledge base with more than 300 thousand medical terms and their descriptions is firstly constructed to store the structured medical knowledge data, and classified with the FastText model. Furthermore, a Word2Vec model is adopted to capture the semantic meanings of words, and the questions and answers are processed with sentence embedding to capture semantic context information. Users’ questions are firstly classified and processed into a sentence vector and a matching algorithm is adopted to match the most similar question. After querying the constructed medical knowledge base, the corresponding answers to previous questions are responded to users. The architecture and flowchart of CQASMD is proposed, which will play an important role in self disease diagnosis and treatment.

Key words: question answering, knowledge base, FastText, sentence embedding, disease diagnosis

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