ISWMbot: Chatbot with an Intent Classification Model using Supervised Algorithm

• Published in: 2024 6th IEEE Symposium on Computers and Informatics, ISCI 2024
• Main Author: Istihat N.N.; Ibrahim Teo N.H.; Roslan R.; Hamzah R.; Shahbudin F.E.; Sulaiman M.S.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204970843&doi=10.1109%2fISCI62787.2024.10667932&partnerID=40&md5=8edf5492925d7f5d8fc3d98c224baef5

Effective solid waste management is essential for environmental best practices, but public participation is hindered by a lack of proper knowledge about waste management. People face difficulties in finding relevant answers about waste management, whether through social media or the internet, leading to time-consuming searches. To address these challenges, the project aims to implement Intent Solid Waste Management Chatbot (iSWMbot), a web-based chatbot, providing users with answers and solutions to their solid waste management queries. The project proposes the implementation of iSWMbot, a user-friendly web-based chatbot designed to provide prompt and relevant answers to users' inquiries on solid waste management. The proposed system utilizes machine learning techniques, incorporating Natural Language Processing for keyword extraction and the Multinomial Naïve Bayes algorithm for classification. The iSWMbot consists of three modules which are query answering, answer suggestions and feedback. The system effectively fulfills its purpose by providing appropriate responses to users' queries and offering helpful suggestions. By implementing the iSWMbot system, it streamlines the workload for waste management authorities and provides timely and accurate information to the public, reducing their concerns and promoting sustainable waste management practices. © 2024 IEEE.