Research On Personalized Information Retrieval System Model Based On Knowledge Map

With the development of information technology,the number of information has exploded.People are increasingly relying on information retrieval systems to find the information they need.Traditional information retrieval is based on the mechanical matching of query and information resources.It often gives a large number of unorganized search results to users.It still requires users to spend time and effort to perform secondary screening,resulting in lower search efficiency.How to break through this dilemma and help users find information they need quickly and accurately is the research emphasis in the field of information retrieval.Based on the theory of knowledge map,our study focuses on the user-centered retrieval method and process,and proposes a personalized information retrieval model consisting of three modules: semantic mining layer,intermediate processing layer and user interface layer.Based on the model,the design and implementation of a personalized retrieval system prototype based on knowledge map was completed.The retrieval system constructed in this study uses the formal concept analysis method to mine the implicit concepts in the information space,identify the relationship between the concepts,and visually display them to the users through the knowledge map.The retrieval system uses the interactive knowledge map as the communication medium between the user and the information space.On the one hand,the interactive knowledge map displays the semantic relationship between the concepts,helps the user to understand the information and explore the information space,and quickly locates the required information;On the other hand,by deeply analyzing the interaction behavior of users and knowledge maps,and supplemented by other requirements identification technologies,the system can accurately identify user needs and push the search results that may be of interest to users.In order to verify the effectiveness of the system in improving the efficiency of user information acquisition and the effectiveness of the experience,we design a comparative experiment of our system and the NetEase public class system.We observe user behavior and preferences when they use the two systems separately,and implement quantitative and qualitative analysis through method such as interviews,statistical analysis methods.Experiments show that compared with the NetEase public class,the users who use the knowledge map-based personalized information retrieval system spend less time on choosing the interest and finding the results they want,also,their search experience is better.It is preliminarily verified that the retrieval system constructed in our study can help users improve the efficiency and experience of obtaining information.