Visit complete Math for Machine Learning roadmap

← Back to Topics List

LSA RESOURCE

LSA (MEANS) : Latent Semantic Analysis

What is Latent Semantic Analysis (LSA)?

  1. Latent Semantic Analysis (LSA) involves creating structured data from a collection of unstructured texts. Before getting into the concept of LSA, let us have a quick intuitive understanding of the concept.
  2. When we write anything like text, the words are not chosen randomly from a vocabulary.
  3. Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.
  4. LSA assumes that words that are close in meaning will occur in similar pieces of text (the distributional hypothesis).
  5. A matrix containing word counts per document (rows represent unique words and columns represent each document) is constructed from a large piece of text and a mathematical technique called singular value decomposition (SVD) is used to reduce the number of rows while preserving the similarity structure among columns.

Resources Community KGx AICbe YouTube

KGX ILLUSTRATION BY AKASTHI [Recovered] KGXperience by Navaneeth malingan

" KGXperience is a community initiative by KGiSL Edu that believes in curating and tinkering with innovation and state of art technologies forging new path in innovation. "

by Devansh Shukla

"AI Tamil Nadu formely known as AI Coimbatore is a close-Knit community initiative by Navaneeth with a goal to offer world-class AI education to anyone in Tamilnadu for free."