Quranic Conversations: Developing a Semantic Search tool for the Quran using Arabic NLP Techniques

Summary

Researchers developed a semantic search tool for the Quran using Arabic NLP techniques. The tool was trained on a dataset of over 30 tafsirs (interpretations) of the Quran. Using the SNxLM model and cosine similarity, the tool identifies Quranic verses most relevant to a user's query, achieving a similarity score of up to 0.97. Why it matters: This tool could significantly improve access to the Quran's teachings for Arabic speakers and researchers, providing a valuable resource for religious study and understanding.