针对科技计划项目评审中项目与专家匹配效率低、效果差的情况,提出构建包含向量空间模型与协同过滤模型的专家智能匹配模型.在提取评审项目组与专家信息特征的基础上,通过向量空间模型产生专家匹配列表,并通过协同过滤模型对匹配列表进行调整优化,从而得到项目与专家匹配结果.以广东省科技计划项目数据为例,开展实验并对模型进行验证,实验结果准确率达97.6%,匹配效果良好.%In the situation of the low efficiency and poor efficiency which existing in the matching process of projects and experts of the scientific and technological project review, the paper proposes an expert intelligent matching model which consists of 2 parts: vector space model and collaborative filtering model.After the feature extraction of each project groups and experts, we generate expert matching list by using vector space model and optimize the matching list using the collaborative filtering model to get a better result.Using the simple data of Guangdong science and technology plan projects and the information of expert database, we design an experiment to test the model and have a good result that the accuracy is 97.6%.
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