计算机工程与应用2016，Vol.52Issue(7)：86-90,5.DOI:10.3778/j.issn.1002-8331.1404-0502
基于词条之间关联关系的文档聚类
Document clustering based on association relations between terms
摘要
Abstract
For the existing vector space model to omit making insufficient semantic relationships between terms in docu-ments representation, this paper proposes a novel document vector representation approach based association relationship. In terms of generalized vector space model, it captures the frequent co-occurrence semantic relations between terms, and then analyzes the correlation between related terms based on association rules, digging out the potential relevance of semantic relationships between terms in the document. It represents documents with linear weighting co-occurrence semantic rela-tions with association semantic. Experimental results show that, compared with the BOW model and GVSM model, the clustering results using association rules document vector represented are more accurate.关键词
文档聚类/关联关系/词条同现/文档相似度/潜在语义Key words
document clustering/association/terms co-occurrence/document similarity/latent semantic分类
信息技术与安全科学引用本文复制引用
任建华,沈炎彬,孟祥福,王伟..基于词条之间关联关系的文档聚类[J].计算机工程与应用,2016,52(7):86-90,5.基金项目
国家青年科学基金（No.61003162）；辽宁省教育厅一般项目（No.L2013131）。 （）
