Hello everyone,
I'm a senior year undergraduate at IGDTUW, New Delhi, India. I am really
interested in working on DBpedia's Chatbot project idea. I am doing a Deep
Learning course these days in which I'm also learning about the use of Deep
Learning in the domain of NLP. I have made a few bots (twitterbot and
facebook messenger chatbot) previously, as hobby projects. I just hope I am
not too late.
I have completed the first two warm up tasks:
https://github.com/rrichajalota/dbpedia-warmup-tasks and currently reading
research papers for the third one.
I have a couple of queries regarding the project idea:
1) "The bot will enhance the capabilities of an underlying question
answering framework to be able to understand and follow a human discourse."
So does this mean that we have to preserve the context of the user query by
using something along the lines of Pattern-action-memory architecture
(which was applied in ELIZA)?
2) "Implement an adaptive interface for a chatbot." What exactly does
adaptive interface imply here? Do we have to make a combination of
retrieval and generative model?
Also, please add me on the slack channel and let me know how I can make
improvements in my warm-up tasks.
Thank you for your time.
Regards,
Rricha Jalota
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