Research On Disease Identification And Personalized Push Of Crops Based On Knowledge Map

With the increase of domestic cereals yield demand and the improvement of computer intelligence technology,cereal disease intelligent recognition attracts more and more attention.The research based on some computer technologies such as web crawler,knowledge mapping,machine learning etc.and focus on cereals disease recognition and customized recommendation situation.The main achievements are as follows:(1)By analyzing data structure of web data source,using breadth priority traversal method to Distributed focal length crawl cereal disease data,and screen large amount of unrelated data judging by web page label.While,using MySQL database stored about 500 cereal disease raw data before crawled,then follow the word frequency extraction method to extract cereal disease characteristics to build cereal disease feature data table,take the highest spot disease word frequency as classification attribute,for instances analysis.(2)By cereal disease entity construction and attribute filling,get multi-featured cereal disease entity,extract semantic relations of cereal diseases to build cereal spot diseases knowledge map relation model.(3)Using decision tree C4.5 and Support Vector Machine(SVM)to build cereal spot diseases classification model,after comparison analyzing,select the best C4.5 model as cereal disease feature classifier.(4)Using MySQL to design a database for cereal spot disease data,using keyword accurate query and cereal disease features query to design a customized recommendation system for cereal disease recognition.