Research Article
Intent Classification using BERT for Chatbot application pertaining to Customer Oriented Services
@INPROCEEDINGS{10.4108/eai.7-12-2021.2314563, author={Dr Geetha N and Mr Vivek G and Vinetia T A}, title={Intent Classification using BERT for Chatbot application pertaining to Customer Oriented Services}, proceedings={Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India}, publisher={EAI}, proceedings_a={ICCAP}, year={2021}, month={12}, keywords={bert intent chat bot neural network contextual go bot}, doi={10.4108/eai.7-12-2021.2314563} }- Dr Geetha N
Mr Vivek G
Vinetia T A
Year: 2021
Intent Classification using BERT for Chatbot application pertaining to Customer Oriented Services
ICCAP
EAI
DOI: 10.4108/eai.7-12-2021.2314563
Abstract
In current scenario, customer interactions with live chat interfaces are very popular and real time customer service are offered in a better way. Traditional human chat services are replaced by conversational agents. The conversational agents or chat bots had become an integral part of business for customer services. Chat bots are the software designed to perform textual or audio conversations with the customers/users. Chat bots provide services with less time but at times fail to meet the customer expectations. Initial days, chat bots are designed by using simple pattern matching and string processing methods using rule-based models. Recently AI based chat bots using machine learning algorithms are developed to handle conversation context. To be more interactive like humans, Conversational AI chat bots are developed with Natural Language Processing (NLP) and Natural Language Understanding (NLU). BERT Model and go Bot are used to identify intent by chat bot and tested using dataset pertaining to networking domain. The results show that the accuracy of conversation is better and can be improved for large dataset.