Exploration on the Ideological and Political Development Dynamics Investigation and Judgment of College Students Considering Big Data Mining Technology

摘要

To Cloud computing has provided a platform for the display and sharing of the big data mining technology (hereinafter referred to as BDMT for short). In order to prevent the leaks of privacy, these data often contain artificially added multi-dimensional information, which makes the big data sharing process face the deep data mining problem. Among them, the exploration on the ideological and political development dynamics investigation and judgment of college students through the network big data is often completed by adopting the generalization processing method on the shared precise large data. As these network big data after processing have obvious characteristics, they can provide conditions for the subsequent accurate inquiry process, which can also ensure the effective analysis on the ideological and political development dynamics investigation and judgment of college students based on these data. Firstly, based on the possible intersection or inclusion relationship between the generalized values, the generalized values are hierarchically clustered. In order to preserve the important information that is related to the ideological and political dynamic set mining of the college students, the algorithm for constructing the big data mining technology is provided. Finally, the feasibility and effectiveness of the big data mining technology are demonstrated through the theoretical analysis and the experimental comparison.