Research On Faceted Search And Information Recommendation Of Online Community Of Chronic Disease Based On Knowledge Graph

With the China's national strength,as well as social affairs continue to improve,while living habits,population aging,and ecological environment have caused the information needs of medical and health issues increased year by year.People's concerns have shifted from survival to life.In particular,the information needs for chronic diseases are highlighted due to the unique characteristics of chronic diseases.The comprehensiveness and complexity of chronic disease prevention,treatment and prognostic factors reflect on the long period,difficulty and heavy burden.How to prevent and treat chronic diseases effectively,the significance of health care information dissemination and practice is very important.With the transformation of medical health concept from disease center to human center,the progress of information service will play an important role in promoting.However,due to the heterogeneity and multi-source of chronic disease resources,it faces great difficulties in obtaining knowledge from information.In particular,the storage and usage of medical health information needs continuously improving.The late establishment of standards lead to the datagenerated by various medical and health institutions cannot be interconnected due to the operation platform,acquisition format and intellectual property rights.In addition,the continuous development of the medical health Internet,distributed,isomerization is a common phenomenon of existing medical health resources.In the face of these resources,the traditional information organization method solves the problems of database storage and simple relationship display to a certain extent,butit does not clearly reflect the content of the explicit and implicit semantic levels.Plus,users cannot compare and use knowledge to solve situations due to their own reasons.Therefore,how to integrate multi-disciplinary methods to meet the needs of users to realize online identification of chronic disease entities,and to use the relationship between entities to construct a graph of chronic disease knowledge,so as to effectively guide the information services in the online community of chronic diseases and better meet the user's medical treatment for chronic diseases have become an urgent problem to be solved.In order to solve the problems of incomplete coverage of existing knowledge graph,unclear application scenarios and poor application effects,this paper builds knowledge graph from multi-source data,and realizes guidance from online community faceted search and resource recommendation.The resources actively acquired by the user and the resource push for the user's explicit needs,in the actual application process of the knowledge map,explore an effective scheme for improving the efficiency of the online information service of the chronic disease.This paper includes seven chapters:The chapter one is the introduction.Based on the comprehensive research status at domestic and abroad,this paper summarizes the shortcomings of current online information retrieval and resource recommendation for chronic diseases,constructs knowledge graph to solve the problem of information organization in online communities of chronic diseases as well as builds a cross-sectional search for online communities of chronic diseases based on knowledge graph.The feasibility of resource recommendation to improve the level of information service,through the research background,research content,technical route and organizational structure,summarizes the research significance and innovation of this paper.The second chapter is about related theories and technical basis.With the help of the existing theory and development techniques of knowledge graph,faceted search and resource recommendation,this paper lays a foundation for solving the scientific research problems of online mapping and resource recommendation of chronic diseases based on knowledge graph.The first part is the definition,development,construction process and the application of deep learning of the knowledge graph.The second part is a conceptual combing and method discussion on faceted search.The third part is an explanation of definition and technical discussion on the recommendation system.The third chapter is the construction of knowledge graph for online communities,which is the cornerstone of the faceted search system.It is mainly to solve the problem of knowledge extraction and fusion.In the actual task,the node and node of the knowledge graph are connected.The paper firstly analyzes the relationship between the entity and attribute,entity and entities.Then it uses the method of machine learning to identify the chronic disease entity,and the fusion of the conceptual map and the integration of the ontology layer in the fusion part.Finally,the knowledge graph is used to realize the visualization operation.The fourth chapter is based on the knowledge graph to build the online community faceted search of chronic diseases.According to the faceted search,there are many problems which resulting in low usage rate.From the faceted analysis to construct content facets and quality facets,faceted sorting,spectral clustering in terms of relationship and semantics to determine the ordering of facets and focus word sorting,and display strategies,etc.,relying on knowledge-rich entities and relationships,increase logicality and utilization of faceted search.The fifth chapter is based on the knowledge graph of online community resource recommendation for chronic diseases.Based on the shortcomings of existing resource recommendation methods,this paper explores the online community resource recommendation principle of chronic diseases from four aspects:information content,information expression,information utility and information source,and deeply analyzes the advantages of knowledge graph in chronic disease online community resource recommendation.Construct a recommendation path for online information of chronic diseases based on knowledge graph.Then,it also constructs different online community resource recommendation modules which based on the user's personalized,similar content and situational awareness.The specific models and algorithms were respectively interpreted.The sixth chapter is based on the knowledge graph of the chronic disease online community faceted search and resource recommendation.Taking diabetes as an example,based on the research of chapters three,four,and five,the demonstration and display of online community faceted search and resource recommendation based on knowledge graph have been realized from information needs from the diabetes online community,diabetes knowledge graph construction for online communities,diabetes online community faceted search based on knowledge graph,and knowledge graph-based diabetes online the community resource recommendation.The chapter seven is summary and outlook.Summarizing the knowledge graph for the online community of chronic diseases,the main content and techniques of online community facet search and resource recommendation based on knowledge graph.Also,it has discussed the problems existing in the research.Finally,the next step of the research has been pointed out.