Author Name Disambiguation made EZ (pronounced as 'Andy-z')

ANDez is an open-source framework that integrates the workflows of several high-performing machine learning (ML) methods for classification and clustering in author name disambiguation (AND). Written in Python and its popular ML packages, ANDez provides a transparent and consistent AND framework that integrates the implementation of multiple intricate procedures from different ML approaches.

By doing so, ANDez enables computer and information science researchers to compare, reuse, and improve existing ML methods of AND to use current methods as baselines in developing new tools. With a simple implementation design, ANDez is also expected to assist scholars who need to analyze ambiguous bibliographic data but lack the skills to write and implement sophisticated ML code.

1. To get the results described in the paper, the code was implemented on Python 3.9.16. To run the code, make sure that all packages in 'requirements.txt' file are installed. You can install them using pip. Type the following command in the terminal or command prompt:

            pip install -r requirements.txt  
   

2. Download four files: 'ANDez.py', 'cluevalmetrics.py', 'modules.py', and 'procedures.py', . Make sure that they are located in the same directory.
   

3. Place your input files into the directory. You can use sample files provided in the data folder.
   

4. Run 'ANDez.py' file.