Mohamed Atef Mosa
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Abstract
The Quran and the hadith of the Prophet are the two sources of legislation for Muslims. Sharia rulings and laws are not only derived from the Quran but also the bulk of them come through hadith. Understanding the hadith, its classification, and verification of its authenticity is vital to reach detailed rulings, as the volume of the hadith is many times greater than the volume of the Quran. As a result, mining in the hadith text is one of the things that has attracted the attention of researchers in the past few years. In this study, we conducted a survey of all the techniques and systems related to the mining of the hadith in its two parts, the Al-Matn and the Al-Sanad. On the other hand, the challenges and obstacles which confronted researchers have been shown; in addition, some suggested tips were highlighted to overcome those challenges. Furthermore, the most essential modern techniques used in the classification of Arabic texts, which gave a high degree of efficiency, were highlighted as milestones for future studies.
- . 2019a. Knowledge discovery in the hadith according to the reliability and memory of the reporters using machine learning techniques. IEEE Access 7 (2019), 157741–157755.Google Scholar
Cross Ref
- . 2019b. Classification of hadith according to its content based on supervised learning algorithms. IEEE Access 7 (2019), 152379–152387.Google ScholarCross Ref
- . 2018. Classification of hadith into positive suggestion, negative suggestion, and information. In Journal of Physics: Conference Series. IOP Publishing 971, 1 (2018), 012046.Google ScholarCross Ref
- . 2012. Novel mechanism to improve hadith classifier performance. In 2012 International Conference on Advanced Computer Science Applications and Technologies (ACSAT). IEEE, 512–517.Google ScholarDigital Library
- . 2020. A superior Arabic text categorization deep model (SATCDM). IEEE Access 8 (2020), 24653–24661.Google ScholarCross Ref
- . 2014. A topical classification of hadith Arabic text. IMAN (2014), 2nd.Google Scholar
- . 2015. Extended topical classification of hadith Arabic text. Int. J. Islam. Appl. Comput. Sci. Technol 3, 3 (2015), 13–23.Google Scholar
- . 2010. Classification of Al-Hadith Al-Shareef using data mining algorithm. In European, Mediterranean and Middle Eastern Conference on Information Systems, EMCIS2010. Abu Dhabi, UAE, 1–23.Google Scholar
- . 2021. Arabic text classification using convolutional neural network and genetic algorithms. IEEE Access 9 (2021), 91670–91685.Google ScholarCross Ref
- . 2021. Predicting semantic categories in text based on knowledge graph combined with machine learning techniques. Applied Artificial Intelligence 35, 12 (2021), 933–951.Google ScholarCross Ref
- . 2022. Feature selection based on ACO and knowledge graph for Arabic text classification. Journal of Experimental & Theoretical Artificial Intelligence (2022), 1–18.Google ScholarCross Ref
- . 2018. Multi-label topic classification of hadith of Bukhari (Indonesian language translation) using information gain and backpropagation neural network. In 2018 International Conference on Asian Language Processing (IALP). IEEE, 344–350.Google ScholarCross Ref
- . 2017. A hybrid method of rule-based approach and statistical measures for recognizing narrators name in hadith. In 2017 6th International Conference on Electrical Engineering and Informatics (ICEEI). IEEE. 1–5.Google ScholarCross Ref
- . 2022. Ontology-based approach to enhance explicit aspect extraction in standard Arabic reviews. International Journal of Computing and Digital Systems 11, 1 (2022), 277–287.Google ScholarCross Ref
- . 2012. Muhadith: A cloud based distributed expert system for classification of ahadith. In 2012 10th International Conference on Frontiers of Information Technology. IEEE, 73–78.Google ScholarDigital Library
- 2016. Evaluating multiple summaries without human models: A first experiment with a trivergent model. In International Conference on Applications of Natural Language to Information Systems. Springer, Cham, 91–101.Google ScholarCross Ref
- . 2020. Arabic text classification using deep learning models. Information Processing & Management 57, 1 (2020), 102121.Google ScholarDigital Library
- , Adiwijaya, and . 2019. Development of rule-based feature extraction in multi-label text classification. Int. J. Adv. Sci. Eng. Inf. Technol. 9, 4 (2019), 1460–1465.Google ScholarCross Ref
- . 2008. Fuzzy expert system in determining Hadith 1 validity. In Advances in Computer and Information Sciences and Engineering. Springer, Dordrecht, 354–359.Google ScholarCross Ref
- . 2009. Neural network for Arabic text classification. In 2009 Second International Conference on the Applications of Digital Information and Web Technologies. IEEE, 778–783.Google ScholarCross Ref
- . 2018. Combined support vector machine and pattern matching for Arabic Islamic hadith question classification system. In International Conference of Reliable Information and Communication Technology. Springer, Cham, 278–290.Google Scholar
- . 2011. Al-Isykaliyyat al-Lughawiyyah fi Tarjamah Ma'ani al-Qur'an al-Karim ila al-Lughah al-Indonisiyyah. TSAQAFAH 7, 1 (2011), 169–190.Google ScholarCross Ref
- . 2022. A new ontology-based method for Arabic sentiment analysis. Big Data and Cognitive Computing 6, 2 (2022), 48.Google ScholarCross Ref
- . 2022. Towards a historical ontology for Arabic language: Investigation and future directions. In International Conference on Intelligent Systems Design and Applications. Springer, Cham, 1078–1087.Google ScholarCross Ref
- . 2017. Query based information retrieval and knowledge extraction using Hadith datasets. In 2017 13th International Conference on Emerging Technologies (ICET). IEEE, 1–6.Google ScholarCross Ref
- . 2022. AR-Sanad 280K: A novel 280K artificial Sanads dataset for hadith narrator disambiguation. Information 13, 2 (2022), 55.Google ScholarCross Ref
- . 2019b. Real-time data text mining based on Gravitational Search Algorithm. Expert Systems with Applications 137 (2019b), 117–129.Google ScholarDigital Library
- . 2020a. A novel hybrid particle swarm optimization and gravitational search algorithm for multi-objective optimization of text mining. Applied Soft Computing 90 (2020a), 106189.Google ScholarCross Ref
- . 2020b. Data text mining based on swarm intelligence techniques: Review of text summarization systems. Trends and Applications of Text Summarization Techniques (2020b), 88–124.Google Scholar
- . 2019a. A survey of multiple types of text summarization with their satellite contents based on swarm intelligence optimization algorithms. Knowledge-Based Systems 163 (2019a), 518–532.Google ScholarCross Ref
- . 2017a. Ant colony heuristic for user-contributed comments summarization. Knowledge-Based Systems 118 (2017a), 105–114.Google ScholarDigital Library
- . 2017b. Graph coloring and ACO based summarization for social networks. Expert Systems with Applications 74 (2017b), 115–126.Google ScholarDigital Library
- 2018. Text categorization on hadith Sahih Al-Bukhari using random forest. In Journal of Physics: Conference Series, Vol. 971. IOP Publishing, 012037.Google ScholarCross Ref
- . 2014. Towards innovative system for Hadith Isnad processing. Int. J. Comput. Trends Technol. 18, 6 (2014), 257–259.Google ScholarCross Ref
- . 2020. A novel hadith processing approach based on genetic algorithms. IEEE Access 8 (2020), 20233–20244.Google ScholarCross Ref
- . 2022. A Hidden Markov Model-based tagging approach for Arabic isnads of Hadiths. Mathematical Problems in Engineering (2022).Google ScholarCross Ref
- . 2005. Al-Hadith text classifier. Journal of Applied Sciences 5, 3 (2005), 584–587.Google ScholarCross Ref
- . 2017. Hadith degree classification for Shahih Hadith identification web based. In 2017 5th International Conference on Cyber and IT Service Management (CITSM). IEEE, 1–6.Google ScholarCross Ref
- . 2017. Question answering system supporting vector machine method for hadith domain. Journal of Theoretical & Applied Information Technology 95, 7 (2017).Google Scholar
- . 2021. Text categorisation in Quran and Hadith: Overcoming the interrelation challenges using machine learning and term weighting. Journal of King Saud University-Computer and Information Sciences 33, 6 (2021), 658–667.Google ScholarCross Ref
- . 2019. Indexing name in hadith translation using hidden Markov model (HMM). In 2019 7th International Conference on Information and Communication Technology (ICoICT). IEEE, 1–5.Google ScholarCross Ref
- . 2011. Verification hadith correctness in Islamic web pages using information retrieval techniques. In Proceedings of International Conference on Information & Communication Systems. 164–167.Google Scholar
- . 2002. A short convergence proof for a class of ant colony optimization algorithms. IEEE Transactions on Evolutionary Computation 6, 4 (2002), 358–365.Google ScholarDigital Library
- . 2019. A deep learning approach for Arabic text classification. In 2019 2nd International Conference on New Trends in Computing Sciences (ICTCS). IEEE, 1–7.Google ScholarCross Ref
- . 2022. Improved sine cosine algorithm with simulated annealing and singer chaotic map for Hadith classification. Neural Computing and Applications 34, 2 (2022), 1385–1406.Google ScholarDigital Library
- . 2021. Text classification of Arabic text: Deep learning in ANLP. In International Conference on Advanced Machine Learning Technologies and Applications. Springer, Cham, 95–103.Google ScholarCross Ref
- . 2019. Narrator's name recognition with support vector machine for indexing Indonesian hadith translations. Procedia Computer Science 157 (2019), 191–198.Google ScholarDigital Library
- . 2019. On the development of a web extension for text authentication on Google Chrome. In 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE). IEEE, 1–5.Google ScholarCross Ref
- . 2018. Development of a web-extension for authentication of online Hadith texts. International Journal of Engineering & Technology 7, 2.5 (2018), 19–22.Google ScholarCross Ref
Index Terms
- An Exhaustive Literature Review of Hadith Text Mining
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