针对P2P环境下采用关键字匹配实现信息检索的不足,引入社会化标签,建立基于语义的个性化推荐模型。首先利用P2P节点用户输入的标签及其类名构建P2P社区的标签本体,显示出标签之间的等级关系,然后通过用户历史标签集与社区标签本体匹配,推荐与用户历史标签集语义相关的标签或资源,最终实现语义推荐。最后对模型进行实例验证。 Aiming at the shortcomings of using keyword matching in P2P environment to retrieve information, a social tag is introduced to establish a personalized recommendation model based on semantic. Firstly, the label body of P2P community is constructed by using the tags input by P2P nodes and their class names, and the hierarchical relation between tags is displayed. Then, the user history tag set matches with the community tag ontology to recommend tags related to semantic of user history tag set Or resources, the ultimate realization of semantic recommendations. Finally, the model is verified by examples.