基于LSI和词典的文本语义相似度算法  

Based on LSI and Dictionary Text Semantic Similarity Algorithm

作　　者：王栋[1] 吴军华[1] 

机构地区：[1]南京工业大学信息科学与工程学院,南京210009

出　　处：《煤炭技术》2010年第12期217-218,共2页Coal Technology

摘　　要：在文本聚类领域里普遍存在一种问题,文本的概念相似度却被忽略。文中利用基于词典和基于文集的本体解决这种问题。还提出一种能合适地抓住相关语义相似度的修改过的隐含语义索引模型。实验结果表明该方法要优于惯用的文本语义相似度算法。The common problem in the fields of text clustering is that the conceptual similarity is ignored.We take thesaurus-based and corpus-based ontology to overcome this problem.A transformed latent semantic indexing（LSI） model which can appropriately capture the associated semantic similarity is proposed and demonstrated as corpus-based ontology.Experiments results show that the method apparently outperforms that with traditional similarity measures.

关 键 词：本体 语义相似度 隐含语义索引 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]