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中文摘要：
文中提出了基于树状结构的语义相似度计算方法．结合概念节点之间的语义关系、语义距离、概念节点的深度、密度对语义相似度的影响，利用树的层次关系来表达概念节点之间的语义信息，并对概念节点密度的计算进行改进，加入了可调节的参数，以适应不同的情景．通过实验验证了该算法在查准率方面具有较强的优越性．
英文摘要：
The paper proposes a new semantic similarity calculation method which is based on tree structure. It combines factors that affect semantic similarity such as the semantic relation between concept nodes, semantic distance, the depth of concept nodes and node density. It uses the tree hierarchy to express the semantic information between concept nodes, and improve the traditional method to compute the density of concept nodes, also joined the adjustable parameters to adapt to different scenarios. At last it is verified this algorithm has a strong advantage by experiments.
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