EFFICIENT CHATBOT DESIGNED TO PROVIDE HEALTH RELATED INFORMATION

Main Article Content

Ratan Singh
Kunal Malvi, Sachin Tollani Priya Jawariya Priyansh K Sakarwal, Vishal Jain

Abstract

An efficient chatbot designed to provide health related information is a system used to chat with the patient  or for any user to provide health related information, which increases the health awareness of user. It works by providing a complete health related info & solution that helps one to self-diagnose their disease to some extent. The proposed system mainly focuses on the user's health problem and their symptoms and then provide necessary info about the disease and its solution. This paper illustrates the improvement of the chatbot enabled website with the features of appointment, and map location.

Downloads

Download data is not yet available.

Article Details

Section
Articles
Author Biography

Ratan Singh

Assistant Professor, Department of Computer Science & Engineering, Geetanjali Institute of Technical Studies, Udaipur, Rajasthan, 313001, India

References

Soo H. Kim, Chang B. Jeong, Hee Kwag, Chin Y. Suen, “Word Segmentation of Printed Word Lines Based on Gap Clustering and Special Symbol Detectionâ€.

Xiaofei Li, Xusheng Xie, “Research of Intelligent Word Segmentation and Information Retrievalâ€, 2nd International Conference on Education Technology and Computer (ICETC)â€, 2010.

Meishan Zhang, Nan Yu, Guohong Fu, “A Simple and Effective Neural Model for Joint Word Segmentation and POS Taggingâ€, 2018.Md. Shakil and Rabindra Nath Nandi.

Mohammed Javed, P. Nagabhushan, B.B. Chaudhari, “A Direct Approach for Word and Character Segmentation in Run-Length Compressed Documents with an Application to Word Spottingâ€, 13th International Conference on Document Analysis and Recognition (ICDAR), 2015.

Naeun Lee, Kirak Kim, Taeseon Yoon, “Implementation of Robot Journalism by Programming Custombot using Tokenization and Custom Taggingâ€, 2017.

Tao Jiang, Hongzhi Yu, Yangkyi Jam, “Tibetan Word Segmentation Systems based on Conditional Random Fieldsâ€, 2011.

Jerome r. Bellagarda, “Parts-Of-Speech tagging by Latent Analogyâ€, IEEE Journal of Selected Topics in Signal Processing, Vol. 4, No. 6, 2010.

Liner Yang, Meishan Zhang, Yang Liu, Maosong Sun, Nan Yu, Guohong Fu, “Joint POS Tagging and Dependency Parsing with Transition-based Neural Networksâ€, 2018.

Ameta, U., Patel, M., Sharma, A.K. (2021). Scrum Framework Based on Agile Methodology in Software Development and Management. In: Mathur, R., Gupta, C.P., Katewa, V., Jat, D.S., Yadav, N. (eds) Emerging Trends in Data Driven Computing and Communications. Studies in Autonomic, Data-driven and Industrial Computing. Springer, Singapore. https://doi.org/10.1007/978-981-16-3915-9_28

Zhenghua Li, Min Zhang, Wanxiang Che, Ting Liu, and Wenliang Chen, “Joint Optimization for Chinese POS Tagging and Dependency Parsingâ€, IEEE/ACM transactions on audio, speech, and language processing, Vol. 22, No. 1, January 2014.

Patel, M., & Sheikh, R. (2019). Handwritten digit recognition using different dimensionality reduction techniques. International Journal of Recent Technology and Engineering, 8(2), 999-1002.

Sijun Qin, Jia Song, Pengzhou Zang, Yue Tan, “Feature Selection for Text Classification Based on Parts-Of-Speech Filter and Synonym Mergeâ€, 12th International Conference on Fuzzy Systems and Knowledge Discover (FSKD), 2015.

Sachin S. Gavankar, Sudhirkumar D. Sawarkar, “Eager Decision Treeâ€, 2nd International Conference for Convergence in Technology (I2CT), 2017.

Naganna Chetty, Kunwar Singh Vaisla, Nagamma Patil, “An improved Method for Disease Prediction using Fuzzy Approachâ€, 2nd International Conference on Advances in Computing and Communication Engineering, 2015.

Kyo-Joong, DongKun Lee, ByungSoo Ko, Ho-Jin, Choi, “A Chatbot for Psychiatric Counseling in Mental Healthcare Service Based on Emotional Dialogue Analysis and Sentence Generationâ€, IEEE 18th International Conference on Mobile Data Management, 2017.

Patel, M., Badi, N., & Sinhal, A. (2019). The role of fuzzy logic in improving accuracy of phishing detection system. International Journal of Innovative Technology and Exploring Engineering, 8(8), 3162-3164.

Sen, S., Patel, M., Sharma, A.K. (2021). Software Development Life Cycle Performance Analysis. In: Mathur, R., Gupta, C.P., Katewa, V., Jat, D.S., Yadav, N. (eds) Emerging Trends in Data Driven Computing and Communications. Studies in Autonomic, Data-driven and Industrial Computing. Springer, Singapore. https://doi.org/10.1007/978-981-16-3915-9_27

H. Gupta and M. Patel, "Study of Extractive Text Summarizer Using The Elmo Embedding," 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2020, pp. 829-834, doi: 10.1109/I-SMAC49090.2020.9243610.

Ashay Argal, Siddharth Gupta, Ajay Modi, Pratik Pandey, Simon Shim, Chang Choo, “Intelligent Travel Chatbot for Predictive Recommendation in Echo Platformâ€.

Oliver Pietquin, Thierry Dutoit, “Dynamic Bayesian Networks for NLU Simulation with Applications to Dialog Optimal Strategy Learningâ€.