Citation Graph Backend

This project is a backend service built with Flask that provides endpoints for searching and retrieving citation data from a citation graph. It utilizes various algorithms such as PageRank and HITS to rank papers based on their citations.

Requirements

• Python 3.6 or higher
• Flask
• Flask-CORS
• NetworkX
• NumPy
• Pickle

Installation

1. Clone the repository:

   git clone <repository-url>
   cd <repository-directory>

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required packages:

   pip install Flask Flask-CORS networkx numpy

4. Download the Dataset:

   • Download the citation dataset from AMiner.
   • After downloading, ensure that the dataset is processed and saved as citation_graph.pkl in the outputs directory.

Running the Application

To run the application, execute the following command:

python app.py

The server will start on http://127.0.0.1:5000/ by default.

API Endpoints

Home

• GET /

  Returns a simple message indicating that the home page is working.

Search

• GET /search

  This endpoint allows you to search for papers based on a query. You can also specify various weights for the ranking algorithms.

  Query Parameters:

  • query: The search term to look for in paper titles.
  • number_of_results: The number of results to return (default is 10).
  • salsa: Weight for the SALSA algorithm (default is 0). - TODO
  • hits: Weight for the HITS algorithm (default is 1).
  • hits_hub: Weight for HITS hub score (default is 1).
  • hits_authority: Weight for HITS authority score (default is 1).
  • pagerank: Weight for the PageRank algorithm (default is 1).
  • semantic_similarity: Weight for semantic similarity (default is 0). - TODO
  • publish_date: Weight for publish date (default is 0). - TODO

  Response: Returns a JSON object containing the search results and the subgraph of citations.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Flask
• NetworkX
• NumPy