Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning Techniques

: Artificial Intelligence (AI) enables machines to be intelligent, most importantly using Machine Learning (ML) in which machines are trained to be able to make better decisions and predictions. In particular, ML-based chatbot systems have been developed to simulate chats with people using Natural L...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: A. Alazzam, Bayan (author)
مؤلفون آخرون: Alkhatib, Manar (author), Shaalan, Khaled (author)
منشور في: 2023
الوصول للمادة أونلاين:https://bspace.buid.ac.ae/handle/1234/3036
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author A. Alazzam, Bayan
author2 Alkhatib, Manar
Shaalan, Khaled
author2_role author
author
author_facet A. Alazzam, Bayan
Alkhatib, Manar
Shaalan, Khaled
author_role author
dc.creator.none.fl_str_mv A. Alazzam, Bayan
Alkhatib, Manar
Shaalan, Khaled
dc.date.none.fl_str_mv 2023
2025-05-14T12:59:18Z
2025-05-14T12:59:18Z
dc.identifier.none.fl_str_mv https://bspace.buid.ac.ae/handle/1234/3036
dc.language.none.fl_str_mv en
dc.title.none.fl_str_mv Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning Techniques
dc.type.none.fl_str_mv Article
description : Artificial Intelligence (AI) enables machines to be intelligent, most importantly using Machine Learning (ML) in which machines are trained to be able to make better decisions and predictions. In particular, ML-based chatbot systems have been developed to simulate chats with people using Natural Language Processing (NLP) techniques. The adoption of chatbots has increased rapidly in many sectors, including, Education, Health Care, Cultural Heritage, Supporting Systems and Marketing, and Entertainment. Chatbots have the potential to improve human interaction with machines, and NLP helps them understand human language more clearly and thus create proper and intelligent responses. In addition to classical ML techniques, Deep Learning (DL) has attracted many researchers to develop chatbots using more sophisticated and accurate techniques. However, research has paid chatbots have widely been developed for English, there is relatively less research on Arabic, which is mainly due to its complexity and lack of proper corpora compared to English. Though there have been several survey studies that reviewed the state-of-the-art of chatbot systems, these studies (a) did not give a comprehensive overview of how different the techniques used for Arabic chatbots in comparison with English chatbots; and (b) paid little attention to the application of ANN for developing chatbots. Therefore, in this paper, we conduct a literature survey of chatbot studies to highlight differences between (1) classical and deep ML techniques for chatbots; and (2) techniques employed for Arabic chatbots versus those for other languages. To this end, we propose various comparison criteria of the techniques, extract data from collected studies accordingly, and provide insights on the progress of chatbot development for Arabic and what still needs to be done in the future.
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network_acronym_str budr
network_name_str The British University in Dubai repository
oai_identifier_str oai:bspace.buid.ac.ae:1234/3036
publishDate 2023
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spelling Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning TechniquesA. Alazzam, BayanAlkhatib, ManarShaalan, Khaled: Artificial Intelligence (AI) enables machines to be intelligent, most importantly using Machine Learning (ML) in which machines are trained to be able to make better decisions and predictions. In particular, ML-based chatbot systems have been developed to simulate chats with people using Natural Language Processing (NLP) techniques. The adoption of chatbots has increased rapidly in many sectors, including, Education, Health Care, Cultural Heritage, Supporting Systems and Marketing, and Entertainment. Chatbots have the potential to improve human interaction with machines, and NLP helps them understand human language more clearly and thus create proper and intelligent responses. In addition to classical ML techniques, Deep Learning (DL) has attracted many researchers to develop chatbots using more sophisticated and accurate techniques. However, research has paid chatbots have widely been developed for English, there is relatively less research on Arabic, which is mainly due to its complexity and lack of proper corpora compared to English. Though there have been several survey studies that reviewed the state-of-the-art of chatbot systems, these studies (a) did not give a comprehensive overview of how different the techniques used for Arabic chatbots in comparison with English chatbots; and (b) paid little attention to the application of ANN for developing chatbots. Therefore, in this paper, we conduct a literature survey of chatbot studies to highlight differences between (1) classical and deep ML techniques for chatbots; and (2) techniques employed for Arabic chatbots versus those for other languages. To this end, we propose various comparison criteria of the techniques, extract data from collected studies accordingly, and provide insights on the progress of chatbot development for Arabic and what still needs to be done in the future.2025-05-14T12:59:18Z2025-05-14T12:59:18Z2023Articlehttps://bspace.buid.ac.ae/handle/1234/3036enoai:bspace.buid.ac.ae:1234/30362025-05-14T12:59:19Z
spellingShingle Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning Techniques
A. Alazzam, Bayan
title Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning Techniques
title_full Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning Techniques
title_fullStr Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning Techniques
title_full_unstemmed Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning Techniques
title_short Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning Techniques
title_sort Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning Techniques
url https://bspace.buid.ac.ae/handle/1234/3036