A Cluster Analysis Model for PhD Dissertation Quality Based on the Depth Algorithm

Abstract

Doctoral education is an important part of higher education and plays an important role in cultivating  many higher talents for the country. In doctoral education, thesis writing is an indispensable teaching section. The quality of the doctoral thesis will directly affect the graduation of doctoral students. Therefore, the analysis of the quality of the doctoral thesis is a typical aspect of the evaluation of doctoral education work. This paper aims to study the quality clustering analysis of the doctoral dissertation based on the depth algorithm. This paper establishes a doctoral paper quality cluster analysis model based on the depth algorithm and carries out the doctoral paper quality cluster analysis experiment based on this model. After the experiment, the main factors affecting the quality of doctoral dissertation were also analyzed. The conclusion is the following: The accuracy rate of the doctoral paper quality cluster analysis model based on the depth algorithm has reached 88.5%.