%0 Journal Article
	%A Qitao Xie and  Qingquan Zhang and  Xiaofei Zhang and  Di Tian and  Ruixuan Wen and  Ting Zhu and  Ping Yi and  Xin Li
	%D 2021
	%J International Journal of Economics and Management Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 170, 2021
	%T A Context-Centric Chatbot for Cryptocurrency Using the Bidirectional Encoder Representations from Transformers Neural Networks
	%U https://publications.waset.org/pdf/10011865
	%V 170
	%X Inspired by the recent movement of digital currency,
we are building a question answering system concerning the subject
of cryptocurrency using Bidirectional Encoder Representations from
Transformers (BERT). The motivation behind this work is to
properly assist digital currency investors by directing them to
the corresponding knowledge bases that can offer them help and
increase the querying speed. BERT, one of newest language models
in natural language processing, was investigated to improve the
quality of generated responses. We studied different combinations of
hyperparameters of the BERT model to obtain the best fit responses.
Further, we created an intelligent chatbot for cryptocurrency using
BERT. A chatbot using BERT shows great potential for the further
advancement of a cryptocurrency market tool. We show that the
BERT neural networks generalize well to other tasks by applying
it successfully to cryptocurrency.
	%P 150 - 156