为实现在知识产品在线定制过程中任务和知识个体的有效匹配，鉴于传统的基于关键词的匹配技术忽略语义信息的缺点，本文提出了一个基于本体的任务和知识个体匹配模型。首先提出了一种综合改进的概念语义相似度计算方法用以提高概念间的语义相似度计算的准确性，然后将任务信息和知识个体的信息分别抽象为任务概念向量和能力概念向量，通过计算两个概念向量之间的语义相似度，得到任务和知识个体的匹配结果。实验结果表明，该模型具有较高的准确率和召回率，能够为知识产品在线定制提供有效的匹配服务。

To achieve effective matching between tasks and knowledge individuals during the online knowledgebased products customization, and taking the lack of semantic information in the traditional technique based on the keywords into account, the paper presents a model of task and knowledge individual matching based on ontology. Firstly it presents a comprehensive improved method of concept semantics similarity computing to improve accuracy in the concept semantics similarity computation, and then abstracts the task and knowledge individual’s information to be the task concept vector and skill concept vector, and gets the matching result of tasks and knowledge individuals by computing the semantic similarity between double concept vectors. The testing result shows that the model can obtain high precision and recall rates, and can provide effective matching services during the online knowledgebased product customization.