Artificial Intelligence based Chatbot: A Case Study
Keywords:Chatbot, Artificial Intelligence, Natural Language Processing
This paper shows the implementation of an artificial intelligent chatterbot with human interaction. Our paper will now tap into the aspects of artificial intelligence because we are designing a smart chatbot and of course, using machine learning to do so and deep learning which is involving more in-depth concepts of artificial intelligence and tapping into the territory of unsupervised learning from data more with the help of neural net-works and more complicated models which help with studying better the unstructured or the unlabeled form of data. The name of our Chabot will be finance manager. It will interact with the user efficiently and come up with reasonable responses for their que-ries, we will also have a module to help people with their wellness in our chat bot apart from it just being a plain financial aspect talker for a more refined personal touch to our paper.
K.-J. Oh, D. Lee, B. Ko, and H.-J. Choi, “A chatbot for psychiatric counseling in mental healthcare service based on emotional dialogue analysis and sentence generation,” in 2017 18th IEEE International Conference on Mobile Data Management (MDM), 2017, pp. 371–375.
S. J. du Preez, M. Lall, and S. Sinha, “An intelligent web-based voice chat bot,” in IEEE EUROCON 2009, 2009, pp. 386–391.
B. Setiaji and F. W. Wibowo, “Chatbot using a knowledge in database: Human-to-machine conversation modeling,” in 2016 7th International Conference on Intelligent Systems, Modelling and Simulation (ISMS), 2016, pp. 72–77.
C.P. Shabariram, V. Srinath, C.S. Indhuja, Vidhya (2017). Ratatta: Chatbot Application Using Expert System, International Journal of Advanced Research in Computer Science and Software Engineering,2017
Mrs Rashmi Dharwadkar1, Dr.Mrs. Neeta A. Deshpande, A Medical ChatBot, International Journal of Computer Trends and Technology (IJCTT) Volume 60 Issue 1-June 2018
Farheen Naaz, Farheen Siddiqui, modified n-gram basedmodel for identifying and filtering near-duplicatedocuments de-tection, International Journal of Advanced Computational Engineering and Networking, ISSN: 2320-2106, Volume-5, Issue-10, Oct.-2017
S. Kumar et al., “Novel method for safeguarding personal health record in cloud connection using deep learning models,” Comput. Intell. Neurosci., vol. 2022, p. 3564436, 2022.
S. Kumar, P. K. Srivastava, G. K. Srivastava, P. Singhal, D. Singh, and D. Goyal, “Chaos based image encryption security in cloud computing,” J. Discrete Math. Sci. Cryptogr., pp. 1–11, 2022.
S. Kumar et al., “Protecting location privacy in cloud services,” J. Discrete Math. Sci. Cryptogr., pp. 1–10, 2022.
Iop.org. [Online]. Available: https://iopscience.iop.org/article/10.1149/10701.15533ecst/meta. [Accessed: 23-Jul-2022].
N-gram Accuracy Analysis in the Method of Chatbot Response, International Journal of Engineering &Technology. (2018)
Aishwarya Hajare, Priyanka Bhosale, Rasika Nanaware,Guruswami Hiremath, Chatbot for education system ISSN:2454-132X, Impact factor: 4.295, Volume 4, Issue 3,IJARIIT.
Ardi, Hario Laskito. “Support Vector Machine Classifier for Sentiment Analysis of Feedback Marketplace with a Compari-son Features at Aspect Level.” (2017).
H. L. Ardi, E. Sediyono, and R. Kusumaningrum, “Support Vector Machine classifier for sentiment analysis of feedback marketplace with a comparison features at aspect level,” Core.ac.uk. [Online]. Available: https://core.ac.uk/download/pdf/141497649.pdf. [Accessed: 23-Jul-2022].
How to Cite
Copyright (c) 2022 Journal of Management and Service Science (JMSS)
This work is licensed under a Creative Commons Attribution 4.0 International License.