In order to enhance the accuracy of retrieved academic papers, so as to facilitate academic research extensively, a series of ranking strategies for academic paper retrieval problem were proposed. Firstly, the heuristic methods based on page ranking algorithm for paper index ranking were described, taking advantage of a Hash indexing technique to effectively reduce memory consumption of the sparse matrix computation. Secondly, the definition of intensive equilibrium value of reference relationship among papers was presented, at the same time, the correlation between iterations of different ranking algorithms and intensive equilibrium value was clarified by a large number of experiments. Finally, the proposed heuristic algorithms for paper index ranking were tested on the SCI index database, and compared with the classical citation descending sort results. The experimental results show that, in the proposed three kind of algorithms based on page ranking techniques, the stochastic process approach with link-structure analysis is much more suitable for the ranking of papers, which obtained by the searching results according to keywords in a certain field.