https://github.com/jannikmaierhoefer/unsupervised-keyword-extraction-methods
A Quantitative Analysis of Unsupervised Keyword Extraction Methods This code is part of a Bachelor thesis at Humboldt University Berlin.
https://github.com/jannikmaierhoefer/unsupervised-keyword-extraction-methods
keybert keyword-extraction rake singlerank textrank yake
Last synced: 6 months ago
JSON representation
A Quantitative Analysis of Unsupervised Keyword Extraction Methods This code is part of a Bachelor thesis at Humboldt University Berlin.
- Host: GitHub
- URL: https://github.com/jannikmaierhoefer/unsupervised-keyword-extraction-methods
- Owner: jannikmaierhoefer
- Created: 2022-05-17T07:40:04.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-06-10T14:17:01.000Z (over 3 years ago)
- Last Synced: 2025-02-15T20:48:17.665Z (8 months ago)
- Topics: keybert, keyword-extraction, rake, singlerank, textrank, yake
- Language: Jupyter Notebook
- Homepage:
- Size: 278 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# A Quantitative Analysis of Unsupervised Keyword Extraction Methods
### This code is part of a Bachelor thesis at Humboldt University Berlin.
This code will compare commonly used unsupervised keyphrase extraction methods, which are structured in three areas:
Statistical methods (TF-IDF, YAKE, RAKE), mathods that are based on graphs (SingleRank, TextRank), and deep learning methods (KeyBERT).
The latter uses language-specific pre-trained models, in this case for German, whereas the statistical and graph-based methods need no training and are language unspecific.