A Mining Algorithm for Relevance of Business Administration Based on Complex Social Information Network

With the rapid development of economy, the reform of business administration system in our country has changed the contents of business administration. Based on this, this paper analyzes the present situation of business administration in our country under the new situation, and advances an algorithm for mining the relevance of business administration based on complex social information network. Through collecting the characteristic behavior of business administration and integrating the structure of complex social information network, this paper analyzes the correlation parameters of business administration behavior. By using the basic idea of association rules mining and extending the traditional methods of co-word analysis and text clustering, a mining model of association rules based on topic keywords and abstract salient words is constructed, and combined with the econometric analysis of related business management behaviors in social information network and Web Science database, the steps of mining association of business management behaviors are optimized. Finally, the experiment proves that the algorithm of mining association of business management behaviors based on complex social information network is highly effective in the practical application and fully meets the research requirements.