基于TreeMiner算法的XML文档结构相似度量方法

提出了一种基于TreeMiner算法挖掘频繁子树的文档结构相似度量方法,解决了传统的距离编辑法计算代价高而路径匹配法无法处理重复标签的问题。该方法架构了一个新的检索模型—频繁结构向量模型,给出了文档的结构向量表示和权重函数,构造了XML文档结构相似度量计算公式;同时从数据结构和挖掘程序上对TreeMiner算法进行了改进,使其更适合大文档数据集的结构挖掘。实验结果表明,该方法具有很高的计算精度和准确率。

An efficient embedding tree matching algorithm based on metaphoric dependency syntax tree

To find out all dependency relationships in which metaphors probably exist between syntax constituents in a given sentence,a dependency tree matching algorithm oriented to Chinese metaphor processing is proposed based on a research of unordered tree inclusion matching.In this algorithm,the pattern library is composed of formalization dependency syntax trees that are derived from large-scale metaphor sentences.These kinds of metaphor sentences are saved in the pattern library in advance.The main process of this algorithm is up-down searching and bottom-up backtracking revising.The algorithm discovers potential metaphoric structures in Chinese sentences from metaphoric dependency pattern library.Finally,the feasibility and efficiency of the new matching algorithm are further testified by the results of a series of experiments on dependency pattern library.Hence,accurate dependency relationships can be achieved through this algorithm.