提出了一种基于《知网》的汉语未登录词语义相似度计算方法。该方法首先参照意合网络理论构造了语义关系匹配函数;接着在用概念图表示未登录词语义信息的基础上,根据节点在语义表示中的作用不同对其分类;然后应用匹配函数对弧、节点对及节点对集进行分类;最后设计了未登录词的整体相似度、不同类型节点对及节点对集相似度的计算方法。该方法能够合理分类未登录词的语义信息并能将其充分利用到计算过程中,实验结果证明此方法是有效的。

A new measure based on HowNet is put forward to compute the semantic similarity between unknown Chinese words. Firstly, the semantic matching function is constructed according the YiHeNet; secondly, nodes in the concept graphs of unknown Chinese words are classified according to their different effects in expressing the semantic information; then, the three notions of arcs, node pairs and node pair sets are classified according to matching functions; finally, similarity measures are designed to compute the similarities of unknown Chinese words, similarities of different node pairs and similarities of different node pair sets. This new measure helps to classify the semantic information of those unknown words and to apply it into the computing course, and experiments prove its effectiveness.
Key wordsHowNet; semantic similarity; unknown words; concept graphs