Abstract: Accurate and objective measurement of the academic achievements of authors and assessment of the academic quality of papers and sites is a vital and challenging task for scientists, research organizations and research funding agencies. Various graph-based ranking methods, such as PageRank, have been widely used to rank authors, papers and places in homogeneous networks, but they are limited to solve this problem in homogeneous networks and are not applicable to heterogeneous networks. Therefore, this paper constructed a multi-entity dynamic heterogeneous academic network based on three entities of author, paper and place, and proposed a new model, MEKI-Rank. In this model, the concept of knowledge inheritance was proposed, that was, the author inherited knowledge from other authors. It extracted seven relationships in the dynamic heterogeneous network at the same time, carried out iterative ranking based on these relationships, and used the results of each round to enhance the ranking of each other.