Patent price evaluation is an important part of intellectual property right transactions. When evaluating patent prices, the impact of the market, law, and technical dimensions on patent prices was not considered effectively by the existing methods. And the market factor of patent plays an important role in the evaluation of patent prices. Aiming at the above problem, an automatic patent price evaluation method based on recurrent neural network was proposed. In this method, based on the market approach, various other factors were considered comprehensively, and the Gated Recurrent Unit (GRU) neural network method was used to realize the automatic evaluation of patent prices. Example tests show that, with the qualitative evaluation results of experts as the benchmark, the average relative accuracy of the proposed method is 0.85. And this average relative accuracy of the proposed method is increased by 3.66%, 4.94% and 2.41% of the average relative accuracies of Analytic Hierarchy Process (AHP), rough set theory method and Back Propagation (BP) neural network method respectively.

In practical application,the patent quality evaluation is usually adopted by experts scoring or the quality evaluation index designed by the experts,so that the evaluation results are subjective and cannot be agreed by the both sides of the evaluation at the same time. In order to solve these problems,a deep learning patent quality evaluation method based on paper similarity calculation was proposed. Firstly,the papers were selected as the objective evaluation data,and the papers were used to calculate the similarity with the patent for augmented data. Then,a deep neural network was introduced to train the quality evaluation model,which was able to realize the map between the similarity of the paper and the quality of the patent to be evaluated. Finally,the quality evaluation model was used to access the patent quality. With perfect score of 100,the simulation results show that in different fields,compared to the corresponding expert evaluation result,the deviation of patent quality evaluation scores obtained by the proposed method is lower than 4,indicating that the proposed method has an effective patent quality evaluation ability.