Verifying Hadith Correctness in Islamic Web Pages using Information Retrieval Techniques

Shatnawi, Mohammed Q.; Abuein, Qusai; Darwish, Omar

doi:10.5120/6327-8680

Cited by 7 publications

(5 citation statements)

References 6 publications

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“…In particular, a tree structure model with a Decision Tree (DT) [43] classifier along with selected attributes of the instances extracted from Hadith books. Rather than relying on building or training a model, Shatnawi et al [44] presented a technique for extracting hadith phrases from web pages and using a positional index created from a database of Hadiths to authenticate Hadiths as Sahih or Daif.…”

Section: Related Workmentioning

confidence: 99%

Fabricated Hadith Detection: A Novel Matn-Based Approach With Transformer Language Models

Gaanoun¹,

Alsuhaibani

2022

IEEE Access

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Muslims rely primarily on the Quran and the Hadiths in all their spiritual life and consider them as sacred sources. If the Quran is God's word, then the Hadiths are God's instructions in the words of the Prophet Muhammad. Since Hadiths are transmitted through multiple narrators, they have been extensively studied to ensure their authenticity. The purpose of this study is to detect fabricated Hadiths, or Mawdu, which is the type of Hadith most rejected by Muslim scholars. The study utilises the central text and content of Hadith, Matn, rather than solely focusing on Hadith chain of narrators, Sanad. In order to accomplish this, we create and release the first dataset dedicated to Mawdu Hadiths, called MAHADDAT. Furthermore, we set up a Mawdu Hadith (MH) detection system based on a transformer language model, BERT, achieving a 92.47% F1 MH score.

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Section: Related Workmentioning

confidence: 99%

Fabricated Hadith Detection: A Novel Matn-Based Approach With Transformer Language Models

Gaanoun¹,

Alsuhaibani

2022

IEEE Access

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“…İşte bu sebeple bahsi geçen çalışmada bu husus sorun oluşturmuş ve araştırmacılar, indekslemenin bir hadis uzmanı ile çalışarak yapılması gerektiği sonucuna varmışlardır. 39 Urduca, Malayca, Endonezyaca ve İngilizce 40 hadis metinlerinin web sayfalarındaki tercümelerine odaklanan ve hadis tercümelerini sahih hadis metinlerine ulaştırmayı hedefleyen çalışmalar ise daha ziyade "varlık ismi tanıma (named entity recognition [NER])" yöntemi üzerinedir. Bu yöntemde bir metnin içerisinde kişi, kurum, yer ve zaman gibi sınıflar, üzerinde çalışılan metnin diline bağımlı olacak şekilde bulunabilmektedir.…”

Section: Hadis Ricâline Yönelik çAlışmalarunclassified

Veri Madenciliği Tekniklerinin ve Algoritmik Araştırmaların Hadis İlmine Uygulanabilirliği

Tombul

2021

Eskiyeni

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In this digital age, the presence of information is felt more and more day by day. When this information circulating in the digital environment is processed and transformed into a highquality form, it will be able to serve for the developing technology age. At this point, data mining methods and algorithmic research that process large amounts of information come into play. Data mining is one of the technologies that is applied and will might be utilized in many fields including natural and social sciences. Such studies, which appear in many scientific disciplines, have also been carried out in the field of hadith, especially within the last twenty years. In this study, the most cited scientific articles that apply data mining methods and algorithmic research to the science of hadith in the world were examined. The studies carried out so far have focused on the the text of the hadith, its rawi (narrator), its authenticity or its use in the web environment. Some of these studies aim to classify the hadiths according to their subjects in general and to create hadith dictionaries in particular. On the other hand, there are studies to systematize the authenticity of the hadith by formulating the chain of narrators and the authentic hadith. In addition there are some studies that evaluate narrators by creating social network graphics. These researches offer the opportunity to present the data in the hadith in a computable and objective way by structuring, as in the sciences. In fact, the hadith scholars (muhaddiths), who aimed to prevent the oblivion and destruction of the sunnah centuries ago, tried to measure and evaluate the knowledge they had acquired on the hadith. From these muhaddiths, we have received some subjective, which are sometimes agreed upon, and sometimes individual evaluations about both the rawi and the text of the hadith. At this point, data mining techniques and algorithmic research will sometimes turn interpretation-based and repetitive information into concrete data. Another opportunity  İntihal Taraması/Plagiarism Detection: Bu makale intihal taramasından geçirildi/This paper was checked for plagiarism Etik Beyan/Ethical Statement: Bu çalışmanın hazırlanma sürecinde bilimsel ve etik ilkelere uyulduğu ve yararlanılan tüm çalışmaların kaynakçada belirtildiği beyan olunur/It is declared that scientific and ethical principles have been followed while carrying out and writing this study and that all the sources used have been properly cited (Sema Tombul).

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“…Besides, Shatnawi [22] asserted that "it is significant to adopt stop-word and stop-list as the accuracy when extracting hadiths from web pages is of outmost importance. The existence of some common phrases in the text of the Hadith limits the precision of the retrieval.…”

Section: Related Workmentioning

confidence: 99%

Generating Arabic Stop-Word for Hadith

Hazzaimeh¹,

Norwawi²,

Khalaf³

2019

MJoSHT

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Stop-words or (function words) play a great role in performing various functions in sentences, but are still typically inadequate to use for retrieval. They consist of several elements such as common nouns, pronouns and prepositions. With that, there are several Arabic particles available in the online Khoja and Abu EL-Khair stoplist taken from various websites. Arabic stop-words’ main problem lies in accepting the prefixes and suffixes’ attachment. In the current paper, a new methodology for generating a general stop-word list has been proposed and applied on hadiths. In detail, hadith is defined as words, acts, deeds, traditions, silent approvals and character of Prophet Muhammad S.A.W. (peace be upon him). The current paper aims at examining the effect of removing stopwords from verification of hadiths. The problem is that the previously generated stop-word lists have been on Modern Standard Arabic (MSA), which is the most commonly used language in hadiths. A stop-word list of Hadith and a corpus-based list has been created to be used in the process of hadith verification. The effectiveness and success of Hadith verification when using the newly generated lists along with earlier generated lists of MSA, combining the Hadith lists have been compared with the MSA lists. The Hadith verification has been performed using sequential pattern mining. Lastly, the experiments have demonstrated that the general lists comprising hadith words showed a better performance compared to using the lists of MSA stopwords.

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Verifying Hadith Correctness in Islamic Web Pages using Information Retrieval Techniques

Cited by 7 publications

References 6 publications

Fabricated Hadith Detection: A Novel Matn-Based Approach With Transformer Language Models

Fabricated Hadith Detection: A Novel Matn-Based Approach With Transformer Language Models

Veri Madenciliği Tekniklerinin ve Algoritmik Araştırmaların Hadis İlmine Uygulanabilirliği

Generating Arabic Stop-Word for Hadith

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