Explicit semantic analysis with R

Explicit semantic analysis (ESA) was proposed by Gabrilovich and Markovitch (2007) to compute a document position in a high-dimensional concept space. At the core, the technique compares the terms of the input document with the terms of documents describing the concepts estimating the relatedness of the document to each concept. In spatial terms if I know the relative distance of the input document from meaningful concepts (e.g. ‘car’, ‘Leonardo da Vinci’, ‘poverty’, ‘electricity’), I can infer the meaning of the document relatively to explicitly defined concepts because of the document’s position in the concept space.


Tuesday, 26 April 2016


Twitter: frbailo



RSS r-bloggers.com

RSS Simply Statistics

RSS Statistical Modeling, Causal Inference, and Social Science

  • The behavioral economists’ researcher degree of freedom
    A few years ago we talked about the two modes of pop-microeconomics: 1. People are rational and respond to incentives. Behavior that looks irrational is actually completely rational once you think like an economist. 2. People are irrational and they … Continue reading →
  • Beverly Cleary is winner in third iteration of Greatest Seminar Speaker competition
    Our third seminar speaker competition has come to an end, with the final round pitting Beverly “Ramona” Cleary against Laura “Ingalls” Wilder. Before going on, I’d like to say that Alison Bechdel is the “Veronica Geng” of this particular competition, … Continue reading →
  • Replacing the “zoo of named tests” by linear models
    Gregory Gilderman writes: The semi-viral tweet thread by Jonas Lindeløv linked below advocates abandoning the “zoo of named tests” for Stats 101 in favor of mathematically equivalent (I believe this is the argument) varieties of linear regression: As an adult … Continue reading →