中文摘要：

专利价值指的是在专利购买交易时的交换价值,它可以为专利的拥有者和购买者提供大量关于专利的珍贵信息,为专利的交易提供决策支持.目前的专利价值评估主要是基于训练或引用的方法.前者过于依赖于人工选择的参数,导致专利价值评估结果的可信度较低;后者往往只考虑了直接引用关联,而忽略了间接引用关联和新颖度对专利价值的影响.针对这些问题,提出一种基于潜在引用网络的专利价值评估方法,并设计了相应的算法来评估各个专利的价值.针对基本算法效率较低的问题,提出了专利价值评估改进算法,极大地提高了专利价值评估的效率.最后,由于新专利加入专利集合时各个专利的价值会发生变化,提出了专利价值评估动态更新算法,用于快速地更新各个专利的价值.实验表明,提出的方法是有效的.

英文摘要：

Patent value refers to the exchange value of a patent in the purchase and transaction.It can provide precious information for the decision-makings of patent owners and buyers.Existing patent value evaluation methods are mainly based on training or citation analysis.However,the methods based on training depend too much on the experimental parameters,which results in weak credibility.On the other hand,the methods based on citation analysis only consider direct citations during the evaluation leaving indirect citations and novelty of patent neglected.For these reasons,this paper presents a latent-citation-network based patent value evaluation method to evaluate the value of each patent in which direct citations,indirect citations and novelty are all considered.First,the latent citation association is discovered utilizing similarity between patents and a latent citation network is established.Then,a basic algorithm is implemented to effectively evaluate the value of each patent on the network.Further,an improved algorithm is proposed to solve the problem of inefficiency of the basic algorithm.Finally,to handle the value variations caused by the arrival of a new patent,a dynamic patent value evaluation algorithm is designed to efficiently update the value of the original patents.As shown in the experiments,the proposed methods in this paper are effective.