一种基于主题的概率文档相关模型

现有文档关系分析模型难以从主题层次上判别文档相关性.为此,提出了一个基于主题的概率文档相关模型(TPDC).TPDC借助Latent Dirichlet Allocation模型学习文档的主题结构;在计算出主题后验概率和主题相似度的基础上推导出文档后验概率;基于文档后验概率构建文档相关性分析模型.实验结果证明,TPDC模型在文档检索精度和文档压缩程度两方面优于向量空间模型,因而更能胜任实际应用中的文档检索任务.

Topic-based Probabilistic Document Correlation Model

Existing models on document relationship analysis have a difficulty in learning document correlation from topic level.To overcome this difficulty,a topic-based probabilistic document correlation model(TPDC)was proposed.The model learns the topic structure of a document through the latent dirichlet allocation model,infers the posterior probability of a document by computing the posterior probability of its topics and topic similarity,and then constructs the document correlation model based on the document po...