中文摘要：

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。

英文摘要：

Because of the defect of retrieving information with keywords matching in P2P system, the social-tagging is introduced and a semantic-based personalized recommendation model is built. First,the hierarchical relationships between tags should be revealed in P2P community tag ontology which is built according to the tag and category input by P2P node users. Then, the tags or sources Semantic related to users＇ history tag sets are recommended through matching users＇ history tag sets with community tag ontology to realize the semantic recommendation. Finally, an example is given to validate the efficiency of the proposed method.