Abstract
With the advancement of technology and the emergence of intelligent machines, the concept of chatbot has come into the scene, which is a computer program that stimulates and processes human conversation, either written or spoken, allowing humans to interact with digital devices as if they were communicating with a real human. The aim of the present work is to make an explicit survey on the state-of-the-art of the chatbot and the methodologies used in the same. Some recent publications have been reviewed from the last 5 years and found that the methodologies used to a great extent were mainly hybrid algorithms, natural language processing, machine learning, and deep learning. As per the survey, the various uses of chatbots have been observed, from educational purpose to business and administration. The main focus of this survey is the use of chatbot in personalized learning systems and the various techniques and methods applied to achieve the same.
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References
Mendoza S et al (2020) Supporting student-teacher interaction through a chatbot. In: International conference on human-computer interaction. Springer, Cham
Bahja M, Hammad R, Hassouna M (2019) Talk2Learn: a framework for chatbot learning. In: European conference on technology enhanced learning. Springer, Cham
Abdul-Kader SA, Woods JC (2015) Survey on chatbot design techniques in speech conversation systems. Int J Adv Comput Sci Appl 6(7)
Setiaji B, Wibowo FW (2016) Chatbot using knowledge in database: human-to-machine conversation modeling. In: 2016 7th international conference on intelligent systems, modeling and simulation (ISMS). IEEE
Clarizia F et al (2018) Chatbot: an education support system for student. In: International symposium on cyber space safety and security. Springer, Cham
Kita T et al (2018) A discussion on effective implementation and prototyping of voice user interfaces for learning activities on moodle. In: CSEDU, no 1
Souali K, Rahmaoui O, Ouzzif M (2018) Introducing traceability based recommendation approach using chatbot for e-learning platforms. In: International conference on advanced intelligent systems for sustainable development. Springer, Cham
Gaglo K et al (2021) Proposal of conversational chatbots for educational remediation in thecontextofcovid-19. 2012. In: 3rd International conference on advanced communication technology (ICACT). IEEE
Pham XL et al (2018) Chatbotas an intelligent personal assistant for mobile language learning. In: Proceedings of the 2018 2nd international conference on education and E-learning 2018
Davies JN et al (2020) Personalization of e-learning process using AI-powered chatbot integration. In: International scientific-practical conference. Springer, Cham
Agrebi M, Sendi M, Abed M (2019) Deep reinforcement learning for personalized recommendation of distance learning. In: World conference on information systems and technologies. Springer, Cham
Shukla VK, Verma A (2019) Enhancing LMS experience through AIML base and retrieval base chatbot using R language. In: 2019 International conference on automation, computational and technology management (ICACTM). IEEE
Rooein D (2019) Data-driven EDU chatbots. In: Companion proceedings of the 2019 world wide web conference
Souali K et al (2019) Recommending moodle resources using chatbots. In: 201915th International conference on signal-image technology &internet-based systems (SITIS). IEEE
Rajkumar R, Ganapathy V (2020) Bio-inspiring learning style chatbot inventory using brain computing interface to increase the efficiency of e- learning. IEEE Access 8:67377–67395
Wu EH-K et al (2020) Advantages and constraints of a hybrid model K-12 e-learning assistant chatbot. IEEE Access 8:77788–77801
Modak M et al (2020) Machine learning based learning disability detection using LMS. In: 2020 IEEE 5th international conference on computing communication and automation (ICCCA). IEEE
Ashok M et al (2021) A systematic survey of cognitive chatbots in personalized learning framework. In: 2021 Sixth international conference on wireless communications, signal processing and networking (WiSPNET). IEEE
Mandal L, Bhattacharya S, Basu PN. An approach to incorporate teachers’ individual teaching and evaluation strategies and experience in tutoring model of an Intelligent Tutoring System. Int J Hybrid
Jommanop T, Mekruksavanich S (2019) E-learning recommendation model based on multiple intelligence. In: 201914th International joint symposium on artificial intelligence and natural language processing (iSAI-NLP). IEEE
Bal S et al (2021) An intelligent chatbot for admission system of an educational institute and prediction of user interest in taking admission. In: Proceedings on 2nd global conference on artificial intelligence and applications. CRC Press, Taylor & Francis (InPress)
Baletal S. Sentiment analysis of online reviews for educational institutions
Mandal L et al (2017) Intellimote: a hybrid classifier for classifying learners’ emotion in a distributed e-learning environment. Turkish J Electr Eng Comput Sci 25(3):2084–2095
Nenkov N et al (2016) Artificial intelligence technologies for personnel learning management systems. In: 2016 IEEE 8th international conference on intelligent systems (IS). IEEE
Bal S, Mahanta S, Mandal L (2021) Bilingual machine translation: Bengali to English. In: Proceedings of international conference on computational intelligence, data science and cloud computing: IEM-ICDC2020, vol 62. Springer
Clarizia F et al (2021) E-learning and industry 4.0: A chatbot for training employees. In: Proceedings of fifth international congress on information and communication technology, Springer, Singapore
Mandal L, Dutta S (2021) Chatbot for query processing in E-learning system. In: Proceedings of international conference on computational intelligence, data science and cloud computing: IEM-ICDC, vol 62. Springer
Dutta D (2017) Developing an intelligent chat-bot tool to assist high school student’s for learning general knowledge subjects. Georgia Institute of Technology
Tsai C-W et al (2017) Exploring the effects of web-mediated computational thinking on developing students’ computing skills in a ubiquitous learning environment. Interactive Learn Environ 25(6):762–777
Mandal L et al. An affective and adaptive E-learning system: a machine learning based approach.
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Sadhu, S., Burman, A., Mandal, L. (2022). A Systematic Survey of the Chatbot Evolution. In: Mandal, L., Tavares, J.M.R.S., Balas, V.E. (eds) Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-1657-1_25
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DOI: https://doi.org/10.1007/978-981-19-1657-1_25
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