In this episode we introduce a very powerful approach for computing semantic similarity between documents.  Here, the terminology “document” could refer to a web-page, a word document, a paragraph of text, an essay, a sentence, or even just a single word.  Two semantically similar documents, therefore, will discuss many of the same topics while two semantically different documents will not have many topics in common.  Machine learning methods are described which can take as input large collections of documents and use those documents to automatically learn semantic similarity relations. This approach is called Latent Semantic Indexing (LSI) or Latent Semantic Analysis (LSA). Visit us at: www.learningmachines101.com to learn more!