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A New Semantic Similarity Measurement Based on HowNet Concept Tree

机译:基于Hownet概念树的新语义相似性测量

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This paper puts forward a new depth & path-based semantic similarity method to improve the existing meaning-based approaches in HowNet. Firstly, a complete concept tree is constructed on the sememe tree according to the concept definitions in HowNet. Then an improved depth & path algorithm was put forward, in which five adjustable parameters are used to compute the depth and path of concept in concept tree. This method avoids the computation process of complicated meaning similarity and is more intuitive and efficient. The experiment shows that proposed algorithm has achieved an excellent level comparing with the existing word similarity algorithms.
机译:本文提出了一种新的深度和基于路径的语义相似性方法,以提高流浪区现有的基于意义的方法。首先,根据Hownet中的概念定义,在Sememe树上构建完整的概念树。然后提出了一种改进的深度和路径算法,其中五个可调参数用于计算概念树中的概念的深度和路径。该方法避免了复杂含义相似性的计算过程,更直观和有效。实验表明,与现有的单词相似性算法相比,所提出的算法已经实现了优异的水平。

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