Keyword Clustering Python Script

Description:

Effortlessly cluster keywords with our cutting-edge Keyword Clustering Script! Leveraging advanced machine learning techniques, our script processes a list of keywords and groups them based on their semantic similarity. Ideal for SEO professionals, content creators, and digital marketers aiming to organize keywords for campaigns, content strategies, or insights extraction.

Features:

1. Tf-idf Vectorization: Transform your keywords into meaningful numerical vectors that capture the essence of each word.
2. Affinity Propagation Clustering: State-of-the-art clustering algorithm ensures optimal grouping of keywords.
3. CSV Output: Easily obtain your clustered keywords in a well-organized CSV format.
4. UTF-8 Encoding Support: Handle a wide range of characters, ensuring compatibility with diverse keyword lists.

Installation:

1. Ensure you have Python (version 3.7 or above) installed on your machine.
2. Install the required libraries by running:

   pip install numpy scikit-learn

3. Download the clustering.py script and place it in a directory of your choice.
4. Place your keywords.txt file (containing the keywords you wish to cluster, one keyword per line) in the same directory as the script.

Usage:

1. Navigate to the directory containing the clustering.py script using the terminal or command prompt:

   cd path_to_directory

2. Run the script:

   python clustering.py

   Once the script completes its execution, you'll find a clusters.csv file in the same directory. This file contains the clustered keywords, organized by their respective groups.

Notes:

• Ensure that the keywords.txt file is saved with UTF-8 encoding to avoid potential decoding issues.
• For large sets of keywords, the clustering process may take some time. Please be patient and wait for the process to complete.