پژوهشی مروری بر حوزه‌های پردازشی متون روایی
محورهای موضوعی : فناوری اطلاعات و دانشسپیده برادران هزاوه 1 , بهروز مینایی بیدگلی 2 * , محمد ابراهیم شناسا 3 , سید علی حسینی 4
1 - دانشگاه آزاد واحد علوم و تحقیقات تهران
2 - دانشگاه علم و صنعت ایران
3 - دانشگاه آزاد واحد تهران-شمال
4 - دانشگاه علم و صنعت ایران
کلید واژه: حدیث, صحت متن, سند, راوی, پیکره حدیث,
چکیده مقاله :
جهت سهولت و رسیدن به دقت بالاتر و زمان پردازش کمتر، ارزیابی صحت حدیث به روش‌های هوشمند توصیه می‌شود. با توجه به حجم قابل توجه متون روایی و مفاهیم و روابط پیچیده موجود در آنها، تاکنون پژوهش‌های فراوانی در حوزه پردازش خودکار حدیث انجام شده است. در این حوزه، عده‌ای از محققان در زمینه‌های پردازش متن و سند، شیوه‌های هوشمندی را آزمایش کرده‌اند، که با توجه به مرور تحقیقات پیشین، حدود 47% از آنان در خصوص پردازش متن احادیث و 46% در مورد پردازش سند احادیث و 7% در هر دو حوزه پژوهش نموده‌اند. با بررسی 97 پژوهش در حوزه پردازش احادیث، مشخص شد که احادیث در حوزه سنجش صحت متن یا سند یا هر دو مورد، ارزیابی شده‌اند. وظایف پردازش را می‌توان به دسته‌های مختلفی از جمله ساخت هستان‌شناسی، رده‌بندی متن حدیث، تشابهات حدیثی و اعتبارسنجی احادیث طبقه بندی نمود. پرکاربردترین روش پردازشی حدیث، روش بازیابی اطلاعات در حوزه پردازش متن حدیث بوده است.
In order to facilitate and achieve higher precision and less processing time, it is recommended to evaluate the authenticity of hadith by intelligent methods. Due to the huge volume of narrative texts (hadith) and the complex concepts and relationships in them, many researches have been conducted in the field of automatic hadith processing. In this field, some researchers have evaluated intelligent methods in the fields of Matn (text) and Isnad processing, which according to the review of previous researches, about 47% of them in the field of hadith text processing and 46% in the case of Isnad processing of hadiths and 7% have done research in both fields. By examining 97 researches in the field of processing hadiths, it was found that hadiths were evaluated in the field of measuring the accuracy of the text or Isnad or both cases. Processing tasks can be classified into different categories such as ontology construction, hadith text classification, hadith similarities and hadith authentication. The most used hadith processing method has been the information retrieval method in the field of hadith text processing.
[1] ايزدي مباركه، کامران، منتظری، مجتبي، “ملاكهاي نقد حديث از منظر استاد علي اكبر غفاري,” پژوهش دینی، شماره 12، صص 151-169، سال 1384.
[57] مینائی بیدگلی، بهروز، پایگاه اطلاعاتی خبرهء علم رجال، کارشناسی ارشد، وزارت علوم، تحقیقات و فناوری - دانشگاه علم و صنعت، تهران، ایران, 1376.
[2] S. Saad, N. Salim, and H. Zainal, “Islamic knowledge ontology creation,” Int. Conf. Internet Technol. Secur. Trans. ICITST 2009, no. November, 2009, doi: 10.1109/icitst.2009.5402635.
[3] S. Saad, N. Salim, H. Zainal, and S. A. M. Noah, “A framework for Islamic knowledge via ontology representation,” Proc. - 2010 Int. Conf. Inf. Retr. Knowl. Manag. Explor. Invis. World, CAMP’10, no. July 2014, pp. 310–314, 2010, doi: 10.1109/INFRKM.2010.5466897.
[4] A. S. Harrag F, Alothaim A, Abanmy A, Alomaigan F, “Ontology Extraction Approach for Prophetic Narration (Hadith) using Association Rules,” Int. J. Islam. Appl. Comput. Sci. Technol., vol. 1, no. 2, pp. 48–57, 2013, Accessed: Apr. 19, 2021. [Online]. Available: https://www.researchgate.net/publication/285879058_Ontology_Extraction_Approach_for_Prophetic_Narration_Hadith_using_Association_Rules.
[5] A.-S. A. Al-Arfaj A, “Towards ontology construction from Arabic texts – a proposed framework,” IEEE Int. Conf. Comput. Inf. Technol., pp. 737–742, 2014.
[6] M. Ghanem, A. Mouloudi, and M. Mourchid, “Creation and populating of an Islamic knowledge ontology using extraction pattern bootstrapping,” in Third National Day on Engineering, Networks and Telecommunications (NDENT 2015), 2015, pp. 36–39.
[7] A. H. Jaafar, N. C. Pa, A. Hamzah Jaafar, and N. Che Pa, “Hadith Commentary Repository: An Ontological Approach,” Proc. 6th Int. Conf. Comput. Informatics, no. 167, pp. 191–198, 2017, Accessed: Apr. 09, 2021. [Online]. Available: http://www.uum.edu.my.
[8] H. A. Al-Sanasleh and B. H. Hammo, “Building domain ontology: Experiences in developing the prophetic ontology form Quran and Hadith,” in Proceedings - 2017 International Conference on New Trends in Computing Sciences, ICTCS 2017, 2017, vol. 2018-Janua, pp. 223–228, doi: 10.1109/ICTCS.2017.35.
[9] N. Soudani, I. Bounhas, B. Elayeb, and Y. Slimani, “Toward an Arabic ontology for Arabic word sense disambiguation based on normalized dictionaries,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 8842, pp. 655–658, 2014, doi: 10.1007/978-3-662-45550-0_68.
[10] M. Alkhatib, A. A. Monem, K. Shaalan, and S. K. Alkhatib M, Monem AA, “A rich Arabic WordNet resource for al-hadith al-shareef,” in Procedia Computer Science 117, 2017, vol. 117, pp. 101–110, doi: 10.1016/j.procs.2017.10.098.
[11] E. D. Sri Mulyani, N. Nelis Febriani SM, A. Darmawan, R. A. Wiyono, R. Deli Saputra, and D. Rohpandi, “Keyword-Based Hadith Grouping Using Fuzzy C-Means Method,” in 2020 2nd International Conference on Cybernetics and Intelligent System (ICORIS), Oct. 2020, pp. 1–6, doi: 10.1109/ICORIS50180.2020.9320796.
[12] H. Sayoud, “Automatic authorship classification of two ancient books: Quran and Hadith,” Proc. IEEE/ACS Int. Conf. Comput. Syst. Appl. AICCSA, vol. 2014, pp. 666–671, 2014, doi: 10.1109/AICCSA.2014.7073263.
[13] H. M. Hanum, Z. A. Bakar, N. A. Rahman, M. M. Rosli, and N. Musa, “Using Topic Analysis for Querying Halal Information on Malay Documents,” Procedia - Soc. Behav. Sci., vol. 121, no. March, pp. 214–222, 2014, doi: 10.1016/j.sbspro.2014.01.1122.
[14] A.-M. R. Al-Kabi MN, Kanaan G, Al-Shalabi R, Al-Sinjilawi SI, M. N. A.- Kabi, G. Kanaan, R. A.- Shalabi, S. I. A.- Sinjilawi, and R. S. A.- Mustafa, “Al-hadith text classifier,” J. Appl. Sci. 5, vol. 5, no. 3, pp. 584–587, Feb. 2005, doi: 10.3923/jas.2005.584.587.
[15] A.-S. S. Al-Kabi MN, M. N. Al-kabi, and S. I. A.- Sinjilawi, “A comparative study of the efficiency of different measures to classify Arabic text,” Univ. Sharjah J. Pure Appl. Sci., vol. 4, no. 2, pp. 13–26, 2007.
[16] F. Harrag and A. Hamdi-Cherif, “UML Modeling of Text Mining in Arabic Language Application to the Prophetic Traditions ‘Hadiths,’” 1st Int. Symp. Comput. Arab. Lang., no. August, 2007.
[17] F. Harrag and E. El-Qawasmah, “Neural network for Arabic text classification,” 2nd Int. Conf. Appl. Digit. Inf. Web Technol. ICADIWT 2009, pp. 778–783, 2009, doi: 10.1109/ICADIWT.2009.5273841.
[18] F. Harrag, E. El-Qawasmeh, and P. Pichappan, “Improving Arabic text categorization using decision trees,” in 2009 1st International Conference on Networked Digital Technologies, NDT 2009, 2009, no. August, pp. 110–115, doi: 10.1109/NDT.2009.5272214.
[19] F. Harrag, E. El-Qawasmah, and A. M. S. Al-Salman, “Comparing dimension reduction techniques for Arabic text classification using BPNN algorithm,” in Proceedings - 1st International Conference on Integrated Intelligent Computing, ICIIC 2010, 2010, pp. 6–11, doi: 10.1109/ICIIC.2010.23.
[20] K. Jbara, “Knowledge Discovery in Al-Hadith Using Text Classification Algorithm,” J. Am. Sci., vol. 6, no. 11, pp. 485–494, 2010, [Online]. Available: http://www.jofamericanscience.org/journals/am-sci/am0611/58_3936am0611_485_494.pdf.
[21] A. I. Al-Kabi MN, Wahsheh HA, “A topical classification of hadith Arabic text,” 2014.
[22] A.-A. A. Al-Kabi MN, Wahsheh HA, Alsmadi IM, “Extended topical classification of hadith Arabic text,” Int. J. Islam. Appl. Comput. Sci. Technol., vol. 3, no. 3, pp. 13–23, 2015.
[23] K. Faidi, R. Ayed, I. Bounhas, and B. Elayeb, “Comparing Arabic NLP tools for Hadith Classification,” Comput. Sci., 2015.
[24] M. A. Saloot, N. Idris, R. Mahmud, S. Ja’afar, D. Thorleuchter, and A. Gani, “Hadith data mining and classification: a comparative analysis,” Artif. Intell. Rev., vol. 46, no. 1, pp. 113–128, 2016, doi: 10.1007/s10462-016-9458-x.
[25] H. Maraoui, K. Haddar, and L. Romary, Segmentation Tool for Hadith Corpus to Generate TEI Encoding, vol. 845. Springer International Publishing, 2019.
[26] N. Neamah and S. Saad, “Question answering system supporting vector machine method for hadith domain,” J. Theor. Appl. Inf. Technol., vol. 95, no. 7, pp. 1510–1524, 2017.
[27] A. Abdi, S. Hasan, M. Arshi, S. M. Shamsuddin, and N. Idris, “A question answering system in hadith using linguistic knowledge,” Comput. Speech Lang., vol. 60, 2020, doi: 10.1016/j.csl.2019.101023.
[28] N. K. Ismail, N. H. M. Saad, S. B. S. Omar, and T. M. T. Sembok, “2D visualization of terms and documents in Malay language,” in 2013 5th International Conference on Information and Communication Technology for the Muslim World (ICT4M), Mar. 2013, pp. 1–6, doi: 10.1109/ICT4M.2013.6518919.
[29] H. Juzi, A. R. Zadeh, E. Barati, and B. Minaei-Bidgoli, “A new framework for detecting similar texts in Islamic Hadith Corpora,” Lr. Lang. Resour. Eval. Relig. Texts, pp. 38–41, 2012.
[30] F. Harrag, “Text mining approach for knowledge extraction in Sahîh Al-Bukhari,” Comput. Human Behav., vol. 30, pp. 558–566, 2014, doi: 10.1016/j.chb.2013.06.035.
[31] M. K. A. B. Zainudin and R. M. Rias, “M-Hadith: Retrieving Malay Haditli text in a mobile application,” ISCAIE 2012 - 2012 IEEE Symp. Comput. Appl. Ind. Electron., no. Iscaie, pp. 60–63, 2012, doi: 10.1109/ISCAIE.2012.6482069.
[32] A. R. Saeed and S. W. Jaffry, “Information Mining from Muslim Scriptures,” 4th Work. South Southeast Asian NLP (WSSANLP), Int. Jt. Conf. Nat. Lang. Process., no. October, pp. 66–71, 2013.
[33] I. Rasyidi, A. Romadhony, and A. T. Wibowo, “Indonesian Hadith Retrieval System using thesaurus,” Proceeding - 2013 Int. Conf. Comput. Control. Informatics Its Appl. “Recent Challenges Comput. Control Informatics”, IC3INA 2013, pp. 285–288, 2013, doi: 10.1109/IC3INA.2013.6819189.
[34] A. Azmi, F. Alkhalifah, A. Alsaeed, and Y. Barnawi, “Using non-conventional search schemes to retrieve Hadiths,” in 5th International Conference on Arabic Language Processing (CITALA ’14)At: Oujda, Morocco, 2014, no. November, pp. 125–129, [Online]. Available: https://www.researchgate.net/publication/335526746_Using_non-conventional_search_schemes_to_retrieve_Hadiths.
[35] N. A. Rahman, Z. Mabni, N. Omar, H. F. M. Hanum, N. N. A. T. Mohamad Rahim, and R. N. Abd Rahman N, Mabni Z, Omar N, Hanum HFM, “A parallel latent semantic indexing (LSI) algorithm for Malay hadith translated document retrieval,” Int. Conf. Soft Comput. Data Sci. Springer, vol. 545, pp. 154–163, 2015, doi: 10.1007/978-981-287-936-3_15.
[36] P. N. E. Nohuddin and J. M. Zainol Z, Chao KF, Nordin AI, “Keyword based clustering technique for collections of Hadith chapters,” Int. J. Islam. Appl. Comput. Sci. Technol., vol. 4, no. 3, pp. 11–18, 2016, [Online]. Available: https://search.proquest.com/docview/2441978482?accountid=27870%0Ahttp://hm4ze3yc3c.search.serialssolutions.com/directLink?&atitle=Keyword+based+clustering+technique+for+collections+of+Hadith+chapters&author=Nohuddin%2C+Puteri+N.+E.%3Bothers&issn=22894012&.
[37] Nurul Syeilla Syazhween, Nurazzah Abdul Rahman, and Zainab Abu Bakar, “Analyzing search retrieval results on Malay ranslated Hadith text documents,” Int. Conf. Appl. Comput. Math. Sci. Eng. May 2016(ACME), no. June, 2016.
[38] S. Mohamed, O. Hassan, and E. Atwell, “Concept Search Tool for Multilingual Hadith Corpus,” Int. J. Sci. Res., vol. 5, no. 4, pp. 1326–1328, 2016, doi: 10.21275/v5i4.nov162788.
[39] A. Aulia, D. Khairani, and N. Hakiem, “Development of a retrieval system for Al Hadith in Bahasa (case study: Hadith Bukhari),” 2017 5th Int. Conf. Cyber IT Serv. Manag. CITSM 2017, Oct. 2017, doi: 10.1109/CITSM.2017.8089323.
[40] A. Aulia, D. Khairani, R. B. Bahaweres, and N. Hakiem, “WatsaQ: Repository of Al Hadith in Bahasa (Case study: Hadith Bukhari),” in International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), Dec. 2017, vol. 2017-Decem, doi: 10.1109/EECSI.2017.8239077.
[41] S. M. O. Hassan, “Building the Multilingual Hadith Corpus to Enhance Performance of Information Retrieval System for Hadith,” Sudan University of Science and Technology, 2017.
[42] F. Harrag, A. Hamdi-Cherif, A. Al-Salman, and E. ElQawasmeh, “Experiments in Improvement of Arabic Information Retrieval,” in Third International Conference on Arabic Language Processing (CITALA ’09), 2009, pp. 71–81.
[43] S. T. Abd Rahman N, Abu Bakar Z, “Query expansion using thesaurus in improving Malay Hadith retrieval system,” IEEE Int. Symp. Inf. Technol., vol. 3, pp. 1404–1409, 2010.
[44] H. Sayoud, “Author discrimination between the holy Quran and Prophet’s statements,” Lit. Linguist. Comput., vol. 27, no. 4, pp. 427–444, 2012, doi: 10.1093/llc/fqs014.
[45] H. Sayoud, “AUTHORSHIP DISCRIMINATION ON QURAN AND HADITH USING DISCRIMINATIVE LEAVE-ONE-OUT CLASSIFICATION,” 2017. [Online]. Available: http://sayoud.net/.
[46] R. Ayed, I. Bounhas, B. Elayeb, N. B. Ben Saoud, F. Evrard, and E. F. Ayed R, Bounhas I, Elayeb B, Saoud NBB, “Improving Arabic texts morphological disambiguation using a possibilistic classifier,” in 19th International Conference on Application of Natural Language to Information Systems, 2014, vol. 8455 LNCS, pp. 138–147, doi: DOI:10.1007/978-3-319-07983-7_18.
[47] M. Q.Shatnawi, Q. Q. Abuein, and O. Darwish, “Verifying Hadith Correctness in Islamic Web Pages using Information Retrieval Techniques,” Int. J. Comput. Appl., vol. 44, no. 13, pp. 47–50, 2012, doi: 10.5120/6327-8680.
[48] S. Altammami, E. Atwell, and A. Alsalka, “Constructing a bilingual hadith corpus using a segmentation tool,” Lr. 2020 - 12th Int. Conf. Lang. Resour. Eval. Conf. Proc., no. May, pp. 3390–3398, 2020.
[49] S. Saeed, S. Yousuf, F. Khan, and Q. Rajput, “Social network analysis of Hadith narrators,” J. King Saud Univ. - Comput. Inf. Sci., no. xxxx, Feb. 2021, doi: 10.1016/j.jksuci.2021.01.019.
[50] T. Alam and J. Schneider, “Social Network Analysis of Hadith Narrators from Sahih Bukhari,” Nov. 2020, doi: 10.1109/BESC51023.2020.9348299.
[51] J. Makhlouta and H. Harkous, “AUBSarf: Compositional Non-deterministic Finite-state Automata for Arabic Morphological Analysis,” 2010. https://www.researchgate.net/publication/50996104_AUBSarf_Compositional_Non-deterministic_Finite-state_Automata_for_Arabic_Morphological_Analysis (accessed Apr. 22, 2021).
[52] A. Azmi and N. Bin Badia, “iTree - Automating the construction of the narration tree of Hadiths (prophetic traditions),” Proc. 6th Int. Conf. Nat. Lang. Process. Knowl. Eng. NLP-KE 2010, no. September 2010, 2010, doi: 10.1109/NLPKE.2010.5587810.
[53] A. N. Azmi A, A. Azmi, and N. Al Badia, “Mining and Visualizing the Narration Tree of Hadiths (Prophetic Traditions),” Cross-Disciplinary Adv. Appl. Nat. Lang. Process. Issues Approaches, no. January 2011, pp. 493–510, 2012, doi: 10.4018/978-1-60960-741-8.ch029.
[54] A. M. Azmi and N. Bin Badia, “e-Narrator - an application for creating an ontology of Hadiths narration tree semantically and graphically,” Arab. J. Sci. Eng., vol. 35, no. 2 C, pp. 51–68, 2010.
[55] M. A. Siddiqui, M. E. Saleh, and A. A. Bagais, “Extraction and Visualization of the Chain of Narrators from Hadiths using Named Entity Recognition and Classification,” Int. J. Comput. Linguist. Res., vol. 5, no. 1, pp. 14–25, 2014.
[56] N. Alias, N. A. Rahman, N. K. Ismail, Z. M. Nor, and M. N. Alias, “Searching Algorithm of Authentic Chain of Narrators’ in Shahih Bukhari Book,” in 2016 International Conference on Applied Computing, Mathematical Sciences and Engineering (ACME2016), 2016, no. May, pp. 60–66.
[58] T. Helmy and A. Daud, “Intelligent agent for information extraction from arabic text without machine translation,” CEUR Workshop Proc., vol. 687, no. February, 2010.
[59] A. M. Azmi, “A novel method to automatically pass hukm on Hadith,” 5th Int. Conf. Arab. Lang. Process., no. August, pp. 118–124, 2014.
[60] A. HM, “The use of fuzzy logic for exploring the words of the critics of the men of hadith (in Arabic),” in Islamiyyat Al-Ma‘rifa 48, 2008, pp. 103–132.
[61] M. Ghazizadeh, M. H. Zahedi, M. Kahani, and B. Minaei Bidgoli, “Fuzzy expert system in determining hadith validity,” in Advances in Computer and Information Sciences and Engineering, 2008, pp. 354–359, doi: 10.1007/978-1-4020-8741-7_64.
[62] H. M. Alrazou, “Data mining application on the resources of Islamic knowledge (in Arabic),” Alukah, 2008.
[63] Z. A. Aldhaln KA, Zeki AM, “Datamining and Islamic knowledge extraction: al-hadith as a knowledge resource,” IEEE Int. Conf. Inf. Commun. Technol. Muslim World (ICT4M ’10), pp. 11–21, 2010.
[64] N. K. Ibrahim, M. F. Noordin, S. Samsuri, M. S. A. Seman, and A. E. M. B. Ali, “Isnad Al-hadith computational authentication: An analysis hierarchically,” Proc. - 6th Int. Conf. Inf. Commun. Technol. Muslim World, ICT4M 2016, pp. 344–349, 2017, doi: 10.1109/ICT4M.2016.68.
[65] A. H. Aldhaln K, Zeki A, Zeki A, “Improving knowledge extraction of hadith classifier using decision tree algorithm,” Int. Conf. Inf. Retr. Knowl. Manag. (CAMP ’12), pp. 148–152, 2012.
[66] K. Aldhaln, A. Zeki, and A. Zeki, “Knowledge Extraction In Hadith Using Data Mining Technique,” Int. J. Inf. Technol. Comput. Sci., vol. 2, pp. 13–21, 2012, [Online]. Available: http://www.ijitcs.com/2ndicekmt/Kawther+AAldhaln.php.
[67] A. H. Aldhlan KA, Zeki AM, Zeki AM, “Novel mechanism to improve Hadith classifier performance,” in International Conference on Advanced Computer Science Applications and Technologies (ACSAT ’12), 2012, pp. 512–517.
[68] M. M. Najeeb, “Towards Innovative System for Hadith Isnad Processing,” Int. J. Comput. Trends Technol., vol. 18, no. 6, pp. 257–259, 2014, doi: 10.14445/22312803/ijctt-v18p154.
[69] M. Ghanem, A. Mouloudi, and M. Mourchid, “Classification of Hadiths using LVQ based on VSM Considering Words Order,” Int. J. Comput. Appl., vol. 148, no. 4, pp. 25–28, 2016, doi: 10.5120/ijca2016911077.
[70] M. M. Ahmad and Najeeb, “A Novel Hadith Processing Approach Based on Genetic Algorithms,” IEEE Access, vol. 8, pp. 20233–20244, 2020, doi: 10.1109/ACCESS.2020.2968417.
[71] F. Haque, A. H. Orthy, and S. Siddique, “Hadith Authenticity Prediction using Sentiment Analysis and Machine Learning,” no. March 2021, pp. 1–6, 2021, doi: 10.1109/aict50176.2020.9368569.
[72] M. M. A. Najeeb, “Towards a Deep Leaning-based Approach for Hadith Classification,” Eur. J. Eng. Technol. Res., vol. 6, no. 3, pp. 9–15, Mar. 2021, doi: 10.24018/ejers.2021.6.3.2378.
[73] S. Mahmoud, O. Saif, E. Nabil, M. Abdeen, M. Elnainay, and M. Torki, “AR-Sanad 280K: A Novel 280K Artificial Sanads Dataset for Hadith Narrator Disambiguation,” Inf. 2022, Vol. 13, Page 55, vol. 13, no. 2, p. 55, Jan. 2022, doi: 10.3390/INFO13020055.
[74] Y. M. Dalloul, “An Ontology-Based Approach to Support the Process of Judging Hadith Isnad,” 2012 Int. Conf. Adv. Comput. Sci. Appl. Technol., no. March, pp. 1–108, 2013.
[75] Rebhi S. Baraka; Yehya M. Dalloul, “Building Hadith Ontology to Support the Authenticity of Isnad,” Int. J. Islam. Appl. Comput. Sci. Technol., vol. 2, no. 1, pp. 25–39, 2014.
[76] N. Abd Rahman, N. Alias, N. K. Ismail, Z. Bin Mohamed Nor, and M. N. B. Alias, “An identification of authentic narrator’s name features in Malay hadith texts,” in ICOS 2015 - 2015 IEEE Conference on Open Systems, Jan. 2016, pp. 79–84, doi: 10.1109/ICOS.2015.7377282.
[77] S. S. Balgasem and L. Q. Zakaria, “A hybrid method of rule-based approach and statistical measures for recognizing narrators name in hadith,” Proc. 2017 6th Int. Conf. Electr. Eng. Informatics Sustain. Soc. Through Digit. Innov. ICEEI 2017, vol. 2017-Novem, pp. 1–5, 2018, doi: 10.1109/ICEEI.2017.8312417.
[78] F. Zaraket and J. Makhlouta, “Arabic cross-document NLP for the hadith and biography literature,” 2012, Accessed: Apr. 22, 2021. [Online]. Available: https://www.researchgate.net/publication/283601764_Arabic_cross-document_NLP_for_the_hadith_and_biography_literature.
[79] W. P. Sari, M. A. Bijaksana, and A. F. Huda, “Indexing name in hadith translation using hidden markov model (HMM),” 2019 7th Int. Conf. Inf. Commun. Technol. ICoICT 2019, pp. 1–5, Jul. 2019, doi: 10.1109/ICoICT.2019.8835296.
[80] A. Mahmood, H. U. Khan, Zahoor-Ur-Rehman, and W. Khan, “Query based information retrieval and knowledge extraction using Hadith datasets,” Proc. - 2017 13th Int. Conf. Emerg. Technol. ICET2017, vol. 2018-Janua, no. December, pp. 1–6, 2018, doi: 10.1109/ICET.2017.8281714.
[81] I. Bounhas, B. Elayeb, F. Evrard, and Y. Slimani, “Toward a computer study of the reliability of arabic stories,” J. Am. Soc. Inf. Sci. Technol., vol. 61, no. 8, pp. 1686–1705, Aug. 2010, doi: 10.1002/asi.21356.
[82] F. Harrag, E. El-Qawasmeh, and A. M. Salman Al-Salman, “Extracting named entities from prophetic narration texts (Hadith),” Commun. Comput. Inf. Sci., vol. 180 CCIS, no. PART 2, pp. 289–297, 2011, doi: 10.1007/978-3-642-22191-0_26.
[83] M. Alhawarat, “A domain-based approach to extract Arabic person names using n-grams and simple rules,” Asian J. Inf. Technol., vol. 14, no. 8, pp. 287–293, 2015, doi: 10.3923/ajit.2015.287.293.
[84] M. Bidhendi, “Extracting person names from ancient Islamic Arabic texts,” … Lang. Resour. …, pp. 1–6, 2012, [Online]. Available: http://textmining.noorsoft.org/File/Article/LRE_Rel_1.pdf.
[85] U. Relational and S. I. Hyder, “Towards a Database Oriented Hadith Research Using Relational, Algorithmic and Data-Warehousing Techniques,” Islam. Cult. Q. J. Shaikh Zayed Islam. Cent. Islam. Arab. Stud., vol. 19, no. March, p. 14, 2008, [Online]. Available: https://www.researchgate.net/profile/Syed_Hyder2/publication/281558734_Towards_a_Database_Oriented_Hadith_Research_Using_Relational_Algorithmic_and_Data-Warehousing_Techniques/links/55ede19408aedecb68fc5ed7.pdf.
[86] Y. Yusoff, R. Ismail, and Z. Hassan, “Adopting hadith verification techniques in to digital evidence authentication,” J. Comput. Sci., vol. 6, no. 6, pp. 613–618, 2010, doi: 10.3844/jcssp.2010.613.618.
[87] Z. Shukur, N. Fabil, J. Salim, and S. A. Noah, “Visualization of the hadith chain of narrators,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 7067 LNCS, no. PART 2, pp. 340–347, 2011, doi: 10.1007/978-3-642-25200-6_32.
[88] M. Najeeb, A. Abdelkader, M. Al-Zghoul, and A. Osman, “A Lexicon for Hadith Science Based on a Corpus,” Int. J. Comput. Sci. Inf. Technol., vol. 6, no. 2, pp. 1336–1340, 2015.
[89] M. M. A. Najeeb, “XML database for Hadith and narrators,” Am. J. Appl. Sci., vol. 13, no. 1, pp. 55–63, 2016, doi: 10.3844/ajassp.2016.55.63.
[90] M. M. Najeeb, “Multi-agent system for hadith processing,” Int. J. Softw. Eng. its Appl., vol. 9, no. 9, pp. 153–166, 2015, doi: 10.14257/ijseia.2015.9.9.13.
[91] Najeeb MMA, “Processing of ‘Hadith Isnad’ based on hidden Markov model,” Int. J. Eng. Technol., vol. 6, no. 2, pp. 50–55, 2016.
[92] S. R. Mohammad Najib, N. Abd Rahman, N. Kamal Ismail, N. Alias, Z. Mohamed Nor, and M. N. Alias, “Comparative Study of Machine Learning Approach on Malay Translated Hadith Text Classification based on Sanad,” MATEC Web Conf., vol. 135, pp. 1–9, 2017, doi: 10.1051/matecconf/201713500066.
[93] S. B. Bin Rodzman et al., “Experiment with text summarization as a positive hierarchical fuzzy logic ranking indicator for domain specific retrieval of Malay translated hadith,” in ISCAIE 2019 - 2019 IEEE Symposium on Computer Applications and Industrial Electronics, 2019, pp. 299–304, doi: 10.1109/ISCAIE.2019.8743988.
[94] A. Mahmood, H. U. Khan, M. Ramzan, H. U. Khan, F. K. Alarfaj, and M. Ilyas, “A Multilingual Datasets Repository of the Hadith Content,” Artic. Int. J. Adv. Comput. Sci. Appl., vol. 9, no. 2, 2018, doi: 10.14569/IJACSA.2018.090224.
[95] S. Altammami, E. Atwell, and A. Alsalka, “Text segmentation using n-grams to annotate Hadith corpus,” in Proceedings of the 3rd Workshop on Arabic Corpus Linguistics, 2019, no. July, pp. 31–39, [Online]. Available: https://www.aclweb.org/anthology/W19-5605.
[96] A. M. Abdelghany, H. M. Abdelaal, A. M. Kamr, and P. M. Elkafrawy, “Doc2Vec : An approach to identify Hadith Similarities Doc2Vec : An approach to identify Hadith Similarities,” Aust. J. Basic Appl. Sci., vol. 14, no. 12, pp. 46–53, 2021, doi: 10.22587/ajbas.2020.14.12.5.
[97] H. M. Abdelaal, A. M. Ahmed, W. Ghribi, and H. A. Youness Alansary, “Knowledge Discovery in the Hadith According to the Reliability and Memory of the Reporters Using Machine Learning Techniques,” IEEE Access, vol. 7, pp. 157741–157755, 2019, doi: 10.1109/ACCESS.2019.2944118.
[98] T. Tarmom, E. Atwell, and M. Alsalka, “Deep Learning vs Compression-Based vs Traditional Machine Learning Classifiers to Detect Hadith Authenticity,” Commun. Comput. Inf. Sci., vol. 1577 CCIS, pp. 206–222, 2022, doi: 10.1007/978-3-031-04447-2_14/COVER.