Design And Implementation Of Organization Structure Reasoning System Based On Multi Source Data

Studying the structure of an organization plays an important role in understanding the operation mode of the organization,defining the nature of the organization,discovering its key nodes,discovering the core departments,targeting the important people,judging the operation status of the organization,and depicting the overall picture of the organization.It is widely used in intelligence consultation,business investigation,investment analysis,and cracking down on illegal organizations.The existing organization structure construction algorithms are mostly based on the analysis of a single data source.The disadvantage of this method is that it is difficult to describe the overall structure of the target organization.In response to the above problems,this article puts forward the research goal of the subject,which is to build an organizational structure reasoning system based on multi-source data,including information collection,data analysis,organizational structure reasoning and construction.In terms of data set construction,this paper designs and implements a distributed multi-source organizational structure data collection system,which incrementally obtains valuable data such as news,public resumes,and organization's official website profile from multiple sources.In order to build the basic structure of the target organization,this article designs different data mining methods for semi-structured information such as public resumes and unstructured information such as official website introductions.Among them,for the processing of text data,this paper designs an organization entity and relationship extraction model based on statistics and deep learning.The experimental results show the effectiveness of this method.In order to fuse department relationship diagrams extracted from multiple data sources into the final organizational structure,this paper designs an organizational structure fusion and reasoning algorithm based on equivalent entity fusion and probabilistic graph model inference to infer the structure of the target organization.Finally,this paper designs and implements an organizational structure reasoning system based on multi-source data to meet the needs of users.In this paper,we test the reasoning algorithm of organizational structure on the constructed data set,and the test results show that the accuracy of our method is higher than that of the existing method using a single data source.The performance and stress tests of the designed and implemented organization architecture reasoning system are carried out.The test results show that the system has good concurrent access ability and stability.