Design And Implementation Of Medical Scheme Recommendation System Based On Hybrid Filter

With the development of wireless Internet technology,various types of practical information existing on the Internet continue to grow,and the way people obtain medical health information has also changed.More and more people are no longer eager to see a doctor after the illness,but obtain medical information such as diagnosis and treatment,through the search engine,WeChat public account and other means on the Internet to help themselves make better medical decisions.However,among the massive mass medical service information on the Internet,the problem of excessive information overload and excessive spam is becoming the main obstacle for users to quickly find the information they need.Recommendation system has become one of the most popular ways to solve the problem of information overload.Applying personalized recommendation technology to the medical information field will help patients overcome the obstacles of getting medical help online.Based on the existing medical information system,this paper designs a medical treatment recommendation system that mixes multiple filtering methods to achieve accurate and hierarchical medical treatment recommendations.First of all,thanks to the development of digital medical care,medical institutions databases and medical portals have more and more medical information available,providing data support.Secondly,this paper analyzes the advantages and disadvantages of collaborative filtering and content-based filtering,and uses each of them to solve our problem of recommendation for medical treatment.In addition,this paper also designed a medical evaluation comments sentiment analysis model.According to the doctor's network comments analysis,the recommendation degree was generated to help improve the result.Finally,in the hybrid strategy,the global series and local parallel mixing modes are adopted.Each type of recommendation method relies on different data.When the data that an algorithm relies on is very sparse,the result of independent operation is not high.Therefore,the cooperation of multiple methods can effectively improve the recommendation effect.This paper combines the data characteristics and algorithm structure of medical recommendation,analyzes and designs the system architecture,function module and storage layer,applies the recommendation algorithm based on mixed multiple filtering methods into the medical treatment recommendation.In the system implementation and testing,we deployed a local server development environment based on the WeChat public platform,collected and cleaned the medical data,and invoked the former algorithm to implement the layered medical recommendation service based on simple dialogue interaction.Finally,the offline data experiments show that the proposed hybrid filtering method is better than the traditional collaborative filtering method in the medical field.The hybrid filtering recommendation system designed and implemented in this paper has achieved the expected results in the recommendation of medical treatment.