ClusteringText

A repository for exploring clustering techniques in natural language processing (NLP), with a focus on analyzing textual datasets. This project demonstrates the implementation of unsupervised learning methods to group similar text documents effectively.

Features

• Preprocessing pipeline for text datasets (can preprocess data in Chinese)

• Multiple clustering algorithms (K-Means, MinibatchKmeans, Birch, AffinityPropagation, AgglomerativeClustering, DBSCAN)

• Support for various vectorization methods (VSM, LSI, LDA)

• Easy integration with custom datasets (given text and keywords)

Installation

• Clone the repository:

git clone https://github.com/michellemashutian/clusteringText.git
cd clusteringText

• Install required dependencies:

pip install -r requirements.txt

Usage

Prepare your dataset in txt format with columns containing text data.

Run the main script:

python main.py

Dependencies

gensim==4.3.3
jieba==0.42.1
numpy==2.2.1
scikit_learn==1.6.0

Contact

For any questions or feedback, feel free to reach out via issues or email me at [email protected]

Happy Clustering!