Large-scale evolutionary knowledge network and multiple integration of university ideological and political education resources based on inference algorithm

Abstract

In the era of big data network, the data is no longer just a simple collection of objects; it contains a wealth of rich, complex, related knowledge. The effective use of the network big data value of the main task is not only to get more and more data, but also need to dig more useful knowledge from the existing data. In this paper, the author analyzes the multiple integration mechanism of ideological and political education resources, by using a KP-LIM inference method on association. Based on empirical analysis, we construct the performance evaluation system of ideological and political education; the result shows that first-class index includes policy implementation (0.25), subject of education (0.15), ideological and political education process (0.2), information system construction (0.15) and environment construction (0.25).College should construct implementation system all-round education of ideological and political education, in order to achieve the multiple integration effect.