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Automation of Admission Enquiry Process Through Chatbot—A Feedback-Enabled Learning System

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Book cover International Conference on Communication, Computing and Electronics Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 637))

Abstract

Chatbots are existing since few years and recently it has started acquiring popularity. Earlier to chatbots, people use help desk as the enquiring medium and hence people working at help desks have to work all the days and answer all the questions. Most of the queries are repetitive in nature and answers are given from a structured database. In order to reduce the effort of humans, we can have a chatbot deployed for the same activity. This work focuses on a chatbot which has been developed to provide a faster human-like interaction for admission enquiry system. The chatbot is capable of handling negative or irrelevant scenarios and responds to the queries in faster manner. Decision making by the chatbot on choosing the right set of sentences is done using LSA algorithm and cosine similarity. In addition to answering, the chatbot also maintains data of questions which is not being answered. This data can be used for future analysis for retrieval-based system. The chatbot also takes the feedback from the customers and this data can be analyzed using the feedback category report generated by the chatbot using LDA algorithm

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References

  1. Aleksandra (Sasha) Kugel Shira David, “Saya ChatBot”, technical paper, 2008

    Google Scholar 

  2. Weizenbaum, J.: ELIZA—a computer program for the study of natural language communication between man and machine. Commun. ACM 9(1) (1966)

    Article  Google Scholar 

  3. Abdul-kader, S.A.: Question Answer System for Online Feedable new born Chatbot, pp. 863–869 (2017)

    Google Scholar 

  4. Herbert, D., Kang, B.H.: Intelligent conversation system using multiple classification ripple down rules and conversational context. Exp. Syst. Appl. 112, 342–352 (2018)

    Article  Google Scholar 

  5. Shukhin, L.M., Borzunov, E.E.: A new Chatbot for customer service on social media. Farm. Zh. 5, 89–91 (1975)

    Google Scholar 

  6. Hardalov, M., Koychev, I., Nakov, P.: Artificial intelligence: methodology, systems, and applications 6304 (2010)

    Google Scholar 

  7. Hussain, S., Athula, G.: Extending a conventional chatbot knowledge base to external knowledge source and introducing user based sessions for diabetes education. In: Proceedings of 32nd IEEE International Conference on Advance. Information Network Application Work. WAINA 2018, vol. 2018, pp. 698–703 (2018)

    Google Scholar 

  8. Serban, I.V., et al.: A Deep Reinforcement Learning Chatbot (Short Version), pp. 1–9. ACM Publications, no. Nips (2018)

    Google Scholar 

  9. Chowanda, A., Chowanda, A.D.: Generative Indonesian conversation model using recurrent neural network with attention mechanism. Procedia Comput. Sci. 135, 433–440 (2018)

    Article  Google Scholar 

  10. Lee, C.-H., Chen, T.-Y., Chen, L.-P., Yang, P.-C., Richard T.-H.: Automatic question generation from Children’s stories for companion Chatbot. In: IEEE International Conference on Information Reuse and Integration for Data Science. 978-1-5386-2660-3, (2018)

    Google Scholar 

  11. Liu, Z.X., Sun, C., Wang, B., Wan, X.: Content-oriented user modeling for personalized response ranking in Chatbots. ACM Trans. Audio, Speech, Lang. Proces. 26(1) (2018)

    Article  Google Scholar 

  12. Io1, H.N., Lee, C.B.: Chatbots and conversational agents: a bibliometric analysis (2017). IEEE 978-1-5386-0948-4/17/2017

    Google Scholar 

  13. Niranjan, M., Saipreethy, M.S., Kumar, T.G.: An intelligent question answering conversational agent using Naïve Bayesian classifier. In: Proceedings of 2012 IEEE International Conference on Technology. Enhancement Education. ICTEE 2012 (2012)

    Google Scholar 

  14. Thomas, N.T.: An e-business chatbot using AIML and LSA. In: International Conference on Advances in Computing, Communications and Informatics (ICACCI) (2016)

    Google Scholar 

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Samyuktha, M., Supriya, M. (2020). Automation of Admission Enquiry Process Through Chatbot—A Feedback-Enabled Learning System. In: Bindhu, V., Chen, J., Tavares, J. (eds) International Conference on Communication, Computing and Electronics Systems. Lecture Notes in Electrical Engineering, vol 637. Springer, Singapore. https://doi.org/10.1007/978-981-15-2612-1_18

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  • DOI: https://doi.org/10.1007/978-981-15-2612-1_18

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  • Print ISBN: 978-981-15-2611-4

  • Online ISBN: 978-981-15-2612-1

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