Natural Language Preprocessings: Prepare text for classification

Natural Language Preprocessings

Natural Language Preprocessings is a Python repository of text-processing recipes for data cleaning, word normalization, stopword removal, tokenization and word-vector preparation, with a Jupyter notebook example for document classification using the Livedoor news corpus.

Independent OpenViST project profile, based on linked sources.

Understand the project

Practical overview

When it fits

Use it when you need Python preprocessing recipes or want to follow its documented Livedoor-based notebook example for document classification.

Who it is for

Python developers building text-preprocessing workflows
NLP learners exploring preprocessing and document classification with a prepared news corpus

Documented uses

Clean and normalize text before downstream analysis.
Remove stopwords and tokenize text for NLP workflows.
Prepare word vectors as part of text analysis.
Follow a notebook-based document-classification example using the Livedoor news corpus.

Before you choose

Requirements & limits

The repository is public and states that it is licensed under MIT.

The classification setup is documented around the Livedoor news corpus.
The repository lists word-vector preparation alongside cleaning, normalization, stopword removal and tokenization.
The documented example uses Python dependencies and Jupyter Notebook.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up the Livedoor document-classification example

Prepare the repository's documented corpus and notebook workflow for the classification example.

Before you start

Python and the repository files
A downloaded and extracted Livedoor news corpus
Jupyter Notebook

Steps

Install the required modules with the command below.
Documented command
```
pip install -r requirements.txt
```
Download and extract the Livedoor news corpus.
From the repository, change to src/data and run the command below.
Documented command
```
python make_dataset.py
```
Start Jupyter Notebook and open notebooks/document_classification.ipynb.

Expected outcome

The documented dataset-preparation stage is complete and the notebook-based document-classification example is available to run.

Guide limitations

The instructions specify the Livedoor news corpus for this example.
The setup instructions do not describe classification results or how to adapt the notebook to other datasets.

Documentation 1 ↗

Evidence and transparency

Sources & review

Official repository ↗

Source record details

Source availability: Active
Sources checked: 16 October 2026
Original website title: Hironsan/natural-language-preprocessings · Official homepage title · retained in its source language

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