中文摘要：

个性化信息服务通过了解用户的兴趣爱好，为不同的用户提供不同的信息服务。XML是一种标示语言，是web文档表示和交换的常用相关标准，因此xML文档之间相似度计算问题对于个性化推荐与信息检索非常重要，为此提出了一个计算XML文档之间的语义和结构相似度的方法XMLSim。首先，基于节点标记对之间的语义相似度和编辑距离计算节点标记对之间的相似度；在分析了路径上节点具有的偏序关系之后，将路径之间相似度问题抽象为最大相似子序列（MSS，Maximal Similar Subsequence）问题，并利用动态规划对MSS问题求解得到路径相似度NpathSim。最后，XML文档之间的相似度XML Sim通过路径集合之间的最大NPathSim的平均值得到。

英文摘要：

XML is a markup language that has emerged as the most relevant standardization effort for document rep- resentation and exchange on the Web. Similarity measure for XML documents plays important role in personalized recommendations and information retrieval. A novel approach to compute semantic and structural similarity between XML documents, XMLSim, is proposed in this paper. Firstly, a similarity between node tags is created based on semantic similarity and string similarity. After analyzing partial relationship among node tags, the path similarity is abstracted as Maximal Similar Subsequence （MSS） problem. The result of NPathSim is obtained by the solution of MSS with dynamic programming. Finally, XMLSim is the average of the best NPathSim value among path sets.