In the process of recommending review experts to projects, in order to effectively make use of the relevance among topics and the relationship among experts, a new method is proposed for review expert recommendation using topic relevance and expert relationship. In this method, firstly, the relevance among topics and the relationships among experts are used to respectively construct the Markov network of topics and the Markov network of experts. Next, the maximum topic clique is extracted from the topic Markov network and the maximum expert clique is extracted from the expert Markov network; then, with the information of the two maximum cliques, the relevance between experts and projects is calculated. After that, according to the descending order of the relevant degree, the candidates are ranked. Finally, the experts, who are the top N to projects, are recommended. The experiments on five domain datasets are made and the results show that the proposed method can improve the effect of review expert recommendation, and the F-value increases by an average of 5% than without considering the relevance among topics and the relationship among experts.

中文翻译：

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一种利用主题相关性和专家关系审查专家推荐的方法

在项目推荐评审专家的过程中，为了有效利用主题间的相关性和专家间的关系，提出了一种利用主题相关性和专家关系进行评审专家推荐的新方法。该方法首先利用主题间的相关性和专家间的关系分别构建主题马尔可夫网络和专家马尔可夫网络。接下来，从主题马尔可夫网络中提取最大主题集团，从专家马尔可夫网络中提取最大专家集团；然后，利用两个最大派的信息，计算专家与项目之间的相关性。之后，根据相关学位的降序对候选人进行排名。最后，专家们，推荐前 N 个项目。在五个领域数据集上进行了实验，结果表明，该方法可以提高审稿专家推荐的效果，与不考虑主题间相关性和专家间关系的情况相比，F值平均提高5%。