Building a semantic inference system for drug consultation–Taking a skin disease as an example

• Main Authors: Tsung-Ching Lin, 林宗慶
• Other Authors: Yu-Liang Chi
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/g4amuv

碩士 === 中原大學 === 資訊管理研究所 === 107 === This study builds a drug consultation system based on semantic inference and mash up of linking data. Use semantic inference for people who need self-medication and they can query the drugs by conceptual way with symptoms or indications. Improving the difficult situations in the past that you need to know the full name of drugs or the drug license numbers. This study transforming web data to web resource. Let machine can understand or identify data and use the linked data mash up the international linked open drug data, make the drug information more complete and diversification. Major research design components of this study include: (1) transforming open data into RDF(Resource Description Framework) format. (2) Establish the knowledge model to achieve the effect of logical inference (3) Build the linked data to mash up the international linked data. The research results show the drug consultation system build in this study can not only query the drugs by conceptual way, but also linked international data to provide the detailed drug information. Combined the semantic web technology and knowledge system. It is more efficient in data integration and fully use the value of data.