摘要
提出了一种基于WordNet和GVSM的文本相似度算法,通过语义的路径长度和路径深度计算两个词的语义相似度,结合改进的GVSM模型计算文本相似度,并对基于TFIDF-VSM模型和本文方法进行了比较。实验结果表明,该算法取得了更好的准确率和效率。
This paper presents a text similarity algorithm based on WordNet and GVSM,computing the similarity of two words by semantics of path length and depth,combined with the improved GVSM model.Then compare the TFIDF-VSM-based model with this method.The experimental results show that this algorithm can achieve a better precision and efficiency.
出处
《微型机与应用》
2011年第3期9-11,共3页
Microcomputer & Its Applications
