Skip to content
This repository has been archived by the owner on Aug 29, 2020. It is now read-only.

A Jupyter notebook on implementation of Latent Semantic Analysis (A Topic Modelling Algorithm) in python.

License

Notifications You must be signed in to change notification settings

iam-mhaseeb/Python-Implementation-of-LSA

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 

Repository files navigation

Python-Implementation-of-LSA

Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual-usage meaning of words by statistical computations applied to a large corpus of text (Landauer and Dumais, 1997). The underlying idea is that the aggregate of all the word contexts in which a given word does and does not appear provides a set of mutual constraints that largely determines the similarity of meaning of words and sets of words to each other. The adequacy of LSA’s reflection of human knowledge has been established in a variety of ways. For example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word–word and passage–word lexical priming data; and, as reported in 3 following articles in this issue, it accurately estimates passage coherence, learnability of passages by individual students, and the quality and quantity of knowledge contained in an essay.

Prerequisites

Things reuired

  1. Jupyter Notebook
  2. Python
  3. Gensim

Getting Started

To use this Code just download the repository & open it up in Jupyter Notebook. The code is ready for your next use, So what are you wating for? Start creating something awesome! Good Luck!

Built With

Contributing

Feel free to submit pull requests to me.

Authors

License

This project is licensed under the MIT License - see the LICENSE file for details

About

A Jupyter notebook on implementation of Latent Semantic Analysis (A Topic Modelling Algorithm) in python.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published