Research And Implementation Of Exploratory Search System On Social Q&A Platform Based On Knowledge Graph

Search has become the main way for people to get information.The current popular search engines offer a one-time interactive search pattern of "asking questions-returning results".When the user does not understand the search target or the search target is not clear enough,it is difficult for the user to find a satisfactory answer from the results provided by this search pattern.Addressing this issue,this paper takes the social question answering platform as the basic data resource,and makes an in-depth study on the process and implementation technology of exploratory search.Based on the idea of iterative interaction of exploratory search.Using knowledge graph to organize data resources and rule-based learning algorithm,a prototype system for exploratory search is designed and presented.The system not only supports regular search behavior,but also assists users in learning.It enables a deeper understanding of the research areas of interest in the learning process,thus constructing more precise query conditions and obtaining satisfactory search results.Combined with the advantages of social Q&A platforms,this paper chooses the educational topics of Zhihu platform as the basic data source of the prototype system,stores the educational data of Zhihu platform for the knowledge map to serve the exploratory search process.The exploratory search system designed and implemented in this paper will effectively solve the problems such as unclear user search goals,traditional search neglect problem context background and inaccurate search results caused by one-time interaction of traditional search engines.The main research of this paper is divided into the following three aspects:Firstly,analyze,collect and sort the data of the social Q&A platform.Use semantic web related techniques to describe and define platform-aware data.This paper uses Stanford seven-step method to construct the data ontology:Above all,define the education topic data of the platform by combining RDFS and FOAF.Then use the graph database Noe4j to store the data to form a knowledge graph.Secondly,this paper analyzes the implementation process of exploratory search and the main points of the search process.And adopts a rule-based learning algorithm,helps record and learn users iteration feedback results.Based on the characteristics of exploratory search and rule-based learning algorithms,this paper further designs the implementation framework of the exploratory search process.Finally,according to the characteristics of the data of the social Q&A platform,a database that uses knowledge maps plus rules to learn to implement an exploratory search system based on knowledge maps.Compared with the process of realizing search results with traditional search engines,and evaluation and verification are carried out from two aspects:questionnaires and comparative arguments.In this paper,the research technology can be realized through the exploratory search system based on the knowledge maps of social Q&A platforms to implemented the exploratory search.Using this system,users can achieve the search goal from fuzzy to clear and then clear the search task.Further develop the ability of users to learn and study a certain field.