LSA(latent semantic analysis)潜在语义分析，也被称为 LSI(latent semantic index)，是 Scott Deerwester, Susan T. Dumais 等人在 1990 年提出来的一种新的索引和检索方法。该方法和传 统向量空间模型(vector space model)一样使用向量来表示词(terms)和文档(documents)，并通 过向量间的关系(如夹角)来判断词及文档间的关系；而不同的是，LSA 将词和文档映射到潜 在语义空间，从
latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture over an un
An Introduction to Latent Semantic Analysis Thomas K Landauer Department of Psychology University of Colorado at Boulder, Peter W. Foltz Department of Psychology New Mexico State University
LDA经典paper 值得一看。We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection is modeled as
Latent Semantic Analysis, Thomas K Landauer, Susan T. Dutnais, 1997; A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge
Latent Variable Modeling with R 英文无水印原版pdf pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书
