基于领域本体的文本过滤模型

目前广为应用的文本过滤技术是利用关键字检索,没有考虑概念之间的关联,因此其过滤性能在达到一定程度后,很难有突破.介绍了一种基于领域本体的文本过滤模型DOTFM,探讨了领域本体在文本过滤中的应用.DOTFM在文本向量的表示和用户模板建立中引入概念关联度,并提出局部型和全局型的文本向量和用户模板.实验结果表明,DOTFM的召回率比之传统的基于关键字的过滤模型有较大提高,而其准确率在合适的阀值时,也有较大提高.

Text filtering model based on domain ontology

The keyword based index is widely used in text filtering,which fails to deal with the relationship between concepts.Conse-quently,when the filtering performance reaches certain degree,it is very difficult to make a breakthrough.This paper introduces a text filtering model called DOTFM,and studies the applications of domain ontology in text filtering.In DOTFM,the concept related degree is introduced as a factor in text vector presentation and user model construction,and the local/global text vector and local...