A Context-Centric Chatbot for Cryptocurrency Using the Bidirectional Encoder Representations from Transformers Neural Networks
Abstract: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.
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