Topic Identification Of Online Doctor Services Reviews Based On Frame Semantics

With the rapid development of the Internet,through advanced big data,cloud computing,networking and other technology,healthcare industry and Internet industry integration,thus contributing to the development of the online healthcare industry.With its low cost and easy operation,online medical care alleviates the problems of inequality of medical resources,difficulty in registering,and expensive medical treatment.The major online medical platforms on the market all provide evaluation windows for doctors and hospitals,and patients can make corresponding evaluations based on the online doctor's diagnosis and treatment work and service quality.At present,online medical service platforms have accumulated a large number of patient evaluations of doctors' diagnosis and treatment.Fine-grained analysis of such evaluation information can help to better understand the patient's satisfaction with doctors' services and refine doctors' services In all aspects,the types of services that patients really care about,thereby alleviating the relationship between doctors and patients,and providing a reference for doctors and hospitals to improve the quality of services.Based on the framework semantics theory,this paper studies the topic identification of doctors' service quality evaluation through the framework semantic annotation of online review data.The research content includes two aspects: the frame semantic analysis of online medical review texts and the topic identification of doctor service quality evaluation.In the frame semantic analysis phase,based on the online medical review data,a frame semantic analysis system is used to integrate the sentiment dictionary for medical evaluation,and a dictionary and rule-based method is used to frame and comment the online reviews.In the stage of doctor service quality evaluation topic identification,firstly,based on the framework and frame elements in the semantic annotation results,referring to the relevant literature in the field of medical service management,a bottom-up summary of doctor service quality evaluation topics is introduced,and the title of doctor service quality evaluation topics is established.Based on the frame semantic annotation,combined with the semantic similarity algorithm,the semantic information in the text is combined with the evaluation topic to identify the evaluation topic in online reviews.The experiment was based on 5000 online doctor reviews,and closed and open testswere performed for frame semantic annotations and doctor service quality evaluation topic identification.The accuracy,recall and F values were used to evaluate the performance of the method.The final experimental results obtained a high accuracy and recall rate,proving the effectiveness of the method,providing a new type of data acquisition and analysis technology for emotional semantic resources in the medical and health field,which is a useful exploration for the development of sentiment analysis into the medical field.