Arabic factoid Question-Answering system for Islamic sciences using normalized corpora
Hajer Maraoui, Kais Haddar, Laurent Romary · Procedia Computer Science · 2021
Factoid Question-Answering (QA) Systems were developed to provide an accurate answer to a factoid question expressed in a natural language. The prime knowledge resources for most of factoid QA systems are online databases. However, the unstructured information in these resources rises the complexity of the information retrieval task. In this paper, we aim to develop an Arabic QA system for factoid questions specialized in Islamic sciences as prophetic tradition (Hadith), Hadith narrator and Quran interpretation (Tafsir). In fact, many questions in the Islamic research fields are focusing on Tafsir and Hadith text. In addition, a number of those interrogations focus on the chain of narrators who transmitted the Hadith. Besides, analyzing the narrator profile is considered an important and enquired task in hadith science. Furthermore, the proposed QA system is based on a normalized database specified in Text Encoding Initiative (TEI) standard. To achieve this, we propose a method composed of three phases to retrieve an accurate answer for the user question. The first phase is the question analysis. The second is the information search. The third phase is the answer processing. Besides, we implant the proposed QA system with a graphic interface allowing the interaction with the user. Finally, we experiment our prototype on 100 questions in the theme of Hadith, narrator and Tafsir text. The QA system succeeds to generate accurate responses for 92% of the entered questions.