民眾到醫院就診時，對於本身初次面對的病徵，在缺乏資訊的情況下，僅能詢問醫院服務人員應至何門診就醫，或自行決定應看什麼門診。根據統計許多民眾到醫院時，面對眾多門診科別時，常不知道要前往何處就醫，且部份民眾初診時有掛錯門診經驗，民眾掛錯門診若情形輕微僅延誤病患時間，情況嚴重將耽誤就醫時效。本研究運用知識工程方法論將複雜醫療疾病及門診資訊整合到本體論中，並以OWL與JessTab 技術完成醫院門診推薦專家系統，且將推薦系統整合到醫院掛號系統中使用，透過網路平臺，使用者可依本身病徵查詢可能罹患疾病、疾病醫療資訊及應就診科別之資訊，提供使用者獲得充分的資訊，協助使用者決策，讓民眾避免掛錯門診。

When people look for clinic at the first time in hospital, they could only ask for help by hospital staff or decide the clinic by themselves due to lack of information. According to some surveys, some people didn't know how to decide the clinic and had experience registering the wrong clinic due to newly diagnosis in hospital. If people make wrong decision for the clinic, it will cause delaying patient's time. Moreover, it will delay the time for medical treatment. The study integrates the medical information into Ontology with knowledge engineering methodology and has finished hospital clinic recommended system by OWL and JessTab technology. People can query the related information of disease and clinic according to symptoms through the hospital network platform. The medical information will help people make the right decision and avoid registering the wrong clinic.