Research And Implementation Of Diabetes Health Education System Based On Semantic Analysis

Semantic Web is an expansion of the current World Wide Web, it can make people and computers collaborate better. Diabetes knowledge retrieval system based on semantic analysis can realize optimal organization and management of diabetes knowledge, and make it possible to help people obtain ideal diabetes knowledge after the Semantic Web technology is applied. Semantic Web-based retrieval mechanism is more intelligent than the traditional keyword-based search, and it can improve precision and recall of resource search.The establishment of Diabetes knowledge ontology is the key to realizing the semantic retrieval. Currently, diabetes affects the lives of many people worldwide. The publicity and outreach of knowledge of diabetes patient lifestyle, preventive maintenance and treatment can greatly improve the patient's quality of life. A user-friendly diabetes health education system is presented based on the establishment of diabetes ontology. Jena is used to implement ontology operation, and it is used to calculate the semantic similarity between the ontology classes. But the semantic similarity is influenced by a variety of factors, and the influence on the semantic similarity from various factors is different. Because the semantic similarity defined by man largely affects the final result, therefore, BP neural network algorithm is used in this article to achieve better similarity algorithm and realize the semantic extensions of keywords that the user inputted. The disadvantage of keyword query and human factors of the semantic similarity algorithm can be improved by this method. It makes the semantic similarity algorithm more efficient, and good search recall and precision can be achieved.Lucene is applied to realize the full-text search technology in the retrieval, index and retrieve the contents of the diabetes resource description library. In order to avoid the limited resources caused by manual annotation, Heritrix crawler is considered here to crawl the knowledge on the basis of the existing web pages, and knowledge of diabetes can be expanded as a result.