Ferdowsi University of Mashhad Information Retrieval Indexing and Retrieval Models
Table of Contents
preprocess text:
- Normalization
- Stemming
- Lemmatization
- Remove stop words
- Remove punctuations
TD-IDF:
- the frequency of words to determine how relevant those words are to a given document.
Libraries:
- pandas
- numpy
- json
- ast
- math
- scipy
- threading
- hazm
- sklearn
Technologies and Tools Utilized in this Project
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
Javid Chaji - @JavidChaji - javid.chaji@gmail.com
Project Link: https://github.com/JavidChaji/FUM-Information-Retrieval-Indexing-and-Retrieval-Models