The Analysis of the Specific Network Content Search Model in Public Policy Formulation

Abstract

The paper focuses on the specific network contents rapid search methods in public policy formulation. When the public policies contain massive amounts of network contents, the components in the public policies will become complex. The diversity of the data features will cause obvious differences in data attribute which will lead low efficiency in searching some specific contents in public policy formulation and cause some difficulties in the search. In order to avoid the defects, this paper proposes a data mining method based on parallel Apriori algorithm which can complete the specific network contents search in public policy formulation. The experiment illustrates the application of the algorithm can optimize the contents search in public policy formulation and effectively increase the efficiency of searching some specific contents in the public policy formulation.