PDF Similarity Matcher

The PDF Similarity Matcher is a command-line tool for finding and displaying PDF documents similar to a given input PDF based on extracted text features. It leverages text extraction and similarity comparison to help you identify relevant matches from a directory of PDFs.

Features

• Extracts text from PDF files.
• Processes and compares features from multiple PDFs.
• Calculates similarity scores between an input PDF and PDFs in the directory.
• Optionally displays detailed key-value feature information for similar PDFs.

Installation

Follow these steps to install and set up the PDF Similarity Matcher:

    pip install pdfsim

Usage

To find similar PDFs, use the following command:

pdfsim -d <directory_containing_pdf> -i <input_pdf> -t <top_n> [-kv]

Arguments

• -d, --database (required): Path to the directory containing PDF files to compare against.
• -i, --input (required): Path to the input PDF file you want to compare.
• -t, --top (optional, default: 1): Number of top similar PDFs to display.
• -kv (optional): Enable detailed key-value feature output for similar PDFs.

Contributing

Follow these steps to setup the project locally

1. Clone the repository:

   git clone https://github.com/yourusername/pdfsim.git
   cd pdfsim

2. Create a virtual environment:

   python3 -m venv venv

3. Activate the virtual environment:

   • On Windows:

     venv\Scripts\activate

   • On macOS/Linux:

     source venv/bin/activate

4. Install the required packages:

   pip install -r requirements.txt

   Ensure requirements.txt includes the necessary libraries:

   PyPDF2
   scikit-learn
   nltk