Knowledge Map Construction And Visualization System Design Based On Public Resource Transaction

After years of development,China's informatization has made certain achievements,the work of 19 major has pointed out the further development of digital information.Public resource transaction is an important part of informatization and play a fair role in government work and market competition.With the massive growth of public resource transaction data,the complex relationship behind the data and the large amount of discrete information make the data not fully utilized.In order to make fully use of data,allocate resources reasonably and assist government decision-making,the analysis and processing of public resource transaction data has deeper practical significance.By building a knowledge map in the field of public resources transaction can mine the data of potential relationship,and form a knowledge network.Based on this,visual display can maximize the role of data resources,offer better service to government work,and build a fair market competition environment.Public resource transaction data as the core,to build knowledge map and break due to the limitation of the traditional data storage media and let the data which is unique,split,discrete,and complex turn to the knowledge network,for providing more accurate services.Multi-dimensional analysis of the bidder's ability,analysis the price trend of different materials in the transaction,analysis the rationality of the user bid amount,and monitor the behavior of public resource trading subjects.The main tasks of this paper are as follows:1.In this paper,there are many data structures in public resource transaction data,the project is complex,and the categories are numerous.The main parties involved are the bidders,and expert groups.The bidding process is cumbersome,and the intermediate data has high redundancy and high contact.This paper analyzes the characteristics and structure of public resource transaction data.And introduce the main information data involved in this article and related data in the bidding process.2.Analyze the key processes and the related data involved in public resources transaction,extract and design the ontology model from the domain data.At the same time,design framework of knowledge extraction and key processes.The key technologies were analyzed and introduced in detail,and the ontology model was generated by Jena to make the OWL file,and the data instance was turned into RDF file by OWL.Finally,the knowledge-based data is stored in the graph database Neo4 j.3.Because of the large amounts of data entity node,and the association rules between nodes and node relationship in the process of knowledge map construction,lead to low efficiency of extraction in the process of calculation.This paper improves a Apriori algorithm based on weight vector matrix reduction,this method selects a subset from the data set as the mining object and gives weight to the elements in the collection.In this paper,the data information is represented by Boolean matrix,the structure of reduction matrix is continuously reduced in the operation,and the generation efficiency of frequent item sets is improved.The test results show that the proposed method can improve the efficiency of the calculation of association rules.4.Constructed the knowledge map of the public resource transaction,and visualized the data with visualization technology.According to the thought of software engineering,the demand analysis,overall design,detailed design,system development and system testing are carried out.