Architectural Design of aChatbotused For Artificial Intelligence with NLP Classification using Deep Learning

Authors

  • Ria Kohli Computer Science, Research Scholar, Bhagwantuniversity Ajmer, Rajasthan, India.
  • Deepak K. Sinha Professor, Department of CSE, Jain(Deemed-to-be University), Bangalore, India
  • G. Nanda Kishor Kumar Professor, Computer Science and Engineering, Malla Reddy University, Telangana, India
  • Badria Sulaiman Alfurhood Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Saudi Arabia
  • Rajesh Gupta Pro Chancellor, Department of Management, Sanskriti University, Mathura, Uttar Pradesh, India https://orcid.org/0000-0002-2118-8474

Keywords:

Chatbot, NLP, Classification, Deep Learning, Normalization, Feature Extraction

Abstract

A chatbot is a piece of technology that uses natural language to mimic human behaviour. In order to improve customer service and happiness, there are many types of chatbots that can be employed as conversational agents in different business fields. This research proposed novel technique in chatbot data based NLP classification utilizing DL structures. Here the information has been gathered from chatbot and handled for clamor expulsion and standardization. The handled information has been highlight extricated with ordered utilizing Bi-LSTM based Intermittent brain organizations. The trial examination has been completed regarding exactness, accuracy, F-1 score.The trials on two data sets of articles revealed that employing natural language processing and the suggested technique established its viability for creating an automatic categorization system of articles with an accuracy of above 91%.

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References

Rahman, M. M., Watanobe, Y., & Nakamura, K. (2021). A bidirectional LSTM language model for code evaluation and repair. Symmetry, 13(2), 247.

Kanungsukkasem, N., &Leelanupab, T. (2019). Financial latent Dirichlet allocation (FinLDA): Feature extraction in text and data mining for financial time series prediction. IEEE Access, 7, 71645-71664.

Suman, S., & Kumar, J. (2022). Interactive Agricultural Chatbot Based on Deep Learning. In Intelligent Data Communication Technologies and Internet of Things (pp. 965-973). Springer, Singapore.

Rahat, F. R., Mim, M., Mahmud, A., Islam, I., Mahbub, M. J. A., Mehedi, M. H. K., &Rasel, A. A. (2022). Data Analysis Using NLP to Sense Human Emotions ThroughChatbot. In International Conference on Advances in Computing and Data Sciences (pp. 64-75). Springer, Cham.

Soufyane, A., Abdelhakim, B. A., & Ahmed, M. B. (2021). An intelligent chatbot using NLP and TF-IDF algorithm for text understanding applied to the medical field. In Emerging Trends in ICT for Sustainable Development (pp. 3-10). Springer, Cham.

Ni, P., Okhrati, R., Guan, S., & Chang, V. (2022). Knowledge Graph and Deep Learning-based Text-to-GQL Model for Intelligent Medical Consultation Chatbot. Information Systems Frontiers, 1-19.

Mittal, M., Battineni, G., Singh, D., Nagarwal, T., & Yadav, P. (2021). Web-based chatbot for frequently asked queries (faq) in hospitals. Journal of Taibah University Medical Sciences, 16(5), 740-746.

Kurup, G., & Shetty, S. D. (2022). AI Conversational Chatbot for Primary Healthcare Diagnosis Using Natural Language Processing and Deep Learning. In Computational Intelligence in Pattern Recognition (pp. 259-272). Springer, Singapore.

Anki, P., Bustamam, A., &Buyung, R. A. (2021). Comparative Analysis of Performance between Multimodal Implementation of Chatbot Based on News Classification Data Using Categories. Electronics, 10(21), 2696.

Bhagchandani, A., &Nayak, A. (2022). Deep Learning Based Chatbot Framework for Mental Health Therapy. In Advances in Data and Information Sciences (pp. 271-281). Springer, Singapore.

Layers of the architecture of a Chatbot that uses artificial intelligence

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Published

30.12.2022

How to Cite

Ria Kohli, Deepak K. Sinha, Kumar, G. N. K. ., Alfurhood, B. S. ., & Gupta, R. . (2022). Architectural Design of aChatbotused For Artificial Intelligence with NLP Classification using Deep Learning. International Journal of Intelligent Systems and Applications in Engineering, 10(3s), 129 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2422

Issue

Vol. 10 No. 3s (2022)

Section

Research Article

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