摘要
词语语义相似度计算是计算机自然语言处理中的关键问题,而相似度计算仅考虑单一的距离因素显然不够合理。通过分析概念网深度和密度因素对相似度计算的影响,提出一种改进的多因素相似度计算方法。实验结果表明,该方法能够根据概念网中节点对的分布状态,调整各影响因素的分配比例,从而使相似度计算结果更趋于合理判断。
Semantic similarity computation is a key issue of computer in natural language processing,while it is clearly not reasonable when only considering the single factor of distance.By analyzing the concept of network depth and density factors on the impact of similarity calculation,an improved similarity measure of multiple factors is proposed.Experimental results show that the concept of network according to the distribution node to adjust the ratio of each factor,which makes the results of similarity calculations more reasonable and judgmental.
出处
《计算机与现代化》
2011年第10期24-26,30,共4页
Computer and Modernization
关键词
语义词典
知网
语义相似度
多因素
semantic dictionary
HowNet
semantic similarity
multi-factor
