Explores the use of ML and NLP to identify canons (qawāʿid), maxims, and substantive principles in Islamic law.
For an analysis of why canons (called qawāʿid in Arabic) are important in Islamic law, see my blog post on it: https://islamiclaw.blog/2020/05/21/canons-qawa%ca%bfid-and-reasoning-in-islamic-law-and-ethics/
For an overview of the motivation behind the semantic similarity and Islamic law experiment, along with the pre-processing steps necessary to get semantic similarity scores, see: https://islamiclaw.blog/2020/06/02/an-experiment-in-natural-language-processing-machine-learning-and-islamic-law-part-1/
For a presentation and interpretation of the results of the experiment, along with thoughts on the future direction of Islamic law and ML/NLP, see:https://islamiclaw.blog/2020/06/02/an-experiment-in-natural-language-processing-machine-learning-and-islamic-law-part-2/
For a YouTube video walking through the Python Jupyter notebook that generated some of the results of the experiment, see: https://www.youtube.com/watch?v=T3UA1jr9O3U