A novel hadith processing approach based on genetic algorithms

Abstract

Quran and Hadith are the main religious sources in Islam. Hadith is mainly the saying of Prophet Mohammad, and it consists of two parts: first is 'Isnad'; which is the series of persons (narrators) who report (narrate) Hadith, and the second is 'Matn'; which is the saying or the narration itself. Isnad can be divided into phrases called 'Isnad-Phrases', which could be tagged according to proposed Part-Of-Isnads (POIs) that represent the entity types of Isnad, such as Narrator Name, Prophet Name and Received Method. One of the main objectives of Hadith sciences is to ascertain the validity of Hadith and determine if it is accepted or rejected; this is known as Hadith judgment. Hadith scholars put many rules to judge Hadiths; some of these rules are related to the chain of narrators. Therefore, to judge Hadith, first, the narrators' names in Isnad should be extracted then judgment rules can be applied. Many researches proposed different methods to extract narrators' names from Isnad. To the best of the author's knowledge, there is no research process Isnad using Genetic Algorithms (GA). In this research, a novel approach is introduced for Isnad processing based on GA. This approach aims to predict the narrators' names and the other POIs for Isnad. The experiments, which conducted on all Hadiths narrated in 'Sahih Muslim' book, show that the proposed approach achieved 81.44% accuracy. For further research in this genre, investigation of utilizing other approaches for Isnad processing, such as deep learning, is recommended.