Hadith data mining and classification: a comparative analysis

Saloot, Mohammad Arshi; Idris, Norisma; Mahmud, Rohana; Jaafar, Salinah; Thorleuchter, Dirk; Gani, Abdullah

doi:10.1007/s10462-016-9458-x

Cited by 54 publications

(34 citation statements)

References 31 publications

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“…In this study, the classification technique and supervised learning algorithms plus combination methods have been used to classify the hadith into different categories, according to its topic. Based on the Sahih al-Bukhari book [5] which contains more than 7500 hadith divided into 96 topics [2], [16]. Also, in this study the combination methods are used such as the Stacking algorithm to improve the classification accuracy using 10-fold crossvalidation method, it includes two levels of classification,…”

Section: Introductionmentioning

confidence: 99%

Classification of Hadith According to Its Content Based on Supervised Learning Algorithms

2019

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Given the importance of the Prophet's Hadith for Muslims all over the world, where it is the second source of Islam after the Qur'an and the fundamental resource of legislation in the Islam community. This study is focused on the Classification of hadith automatically into different categories according to its content, based on Hadith text. The objective of this study is to build a classifier model can classify and differentiate hadith categories, to predict its topic like prayer, fasting, and zakat; using data mining and machine learning techniques. In this study, many supervised learning algorithms plus combination methods such as the stacking algorithm was used to improve classification accuracy. The best three classifiers were evaluated mainly: the Decision Tree (DT), Random Forest (RF), and Naïve Bayes (NB), which achieved higher accuracy reached up to 0.965%, 0.956, and 0.951% respectively. Also, Binary (Boolean algebra) and TF-IDF methods as term weighting was applied to determine the frequency of each word in the hadith text, and identify the most significant features in training dataset using Information Gain (IG), and Chi-square (CHI). The experimental results showed that retrain these classifiers after applying IG and CHI as features selection; gave better accuracy compared to the previous results. Additional to, the best classifier gave high accuracy was DT, it has achieved higher accuracy in most test cases whether in the Boolean algebra or TF-IDF because it can deal with missing values and identifying the most essential features from the training dataset, known as features engineering.

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Section: Introductionmentioning

confidence: 99%

Classification of Hadith According to Its Content Based on Supervised Learning Algorithms

2019

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“…The experimental results showed that the accuracy of Khoja's stemmer and SVM combination was 57.50%; which outperformed the other stemmer and classifier combinations. Saloot et al [17] manage a notable comparative analysis of classification and data mining techniques that have been used for Hadiths. They divided their work into two tracks; one to investigate the researches that emphasis on classification process of Hadiths to some categories like authentic, not authentic, unknown, weak, etc.…”

Section: A Hadith-text Processing Researchesmentioning

confidence: 99%

A Novel Hadith Processing Approach Based on Genetic Algorithms

Najeeb

2020

IEEE Access

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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. INDEX TERMS Arabic natural language processing, genetic algorithms, hadith, isnad, tagging.

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“…However, the three related studies use different data sets, research with latent semantic indexing using Malay language data sets, while vector space models and coefficient tables use Indonesian translated data sets. Therefore, the vector space model was chosen because the dataset used is Indonesian translated and is the best method for conducting retrieval documents [10].…”

Section: Introductionmentioning

confidence: 99%

Improving Document Retrieval with Spelling Correction for Weak and Fabricated Indonesian-Translated Hadith

Ramadhan

Lhaksmana

2020

RESTI

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Hadith has several levels of authenticity, among which are weak (dhaif), and fabricated (maudhu) hadith that may not originate from the prophet Muhammad PBUH, and thus should not be considered in concluding an Islamic law (sharia). However, many such hadiths have been commonly confused as authentic hadiths among ordinary Muslims. To easily distinguish such hadiths, this paper proposes a method to check the authenticity of a hadith by comparing them with a collection of fabricated hadiths in Indonesian. The proposed method applies the vector space model and also performs spelling correction using symspell to check whether the use of spelling check can improve the accuracy of hadith retrieval, because it has never been done in previous works and typos are common on Indonesian-translated hadiths on the Web and social media raw text. The experiment result shows that the use of spell checking improves the mean average precision and recall to become 81% (from 73%) and 89% (from 80%), respectively. Therefore, the improvement in accuracy by implementing spelling correction make the hadith retrieval system more feasible and encouraged to be implemented in future works because it can correct typos that are common in the raw text on the Internet.

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Hadith data mining and classification: a comparative analysis

Cited by 54 publications

References 31 publications

Classification of Hadith According to Its Content Based on Supervised Learning Algorithms

Classification of Hadith According to Its Content Based on Supervised Learning Algorithms

A Novel Hadith Processing Approach Based on Genetic Algorithms

Improving Document Retrieval with Spelling Correction for Weak and Fabricated Indonesian-Translated Hadith

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