Dear Rricha,
the warmup tasks look good to me at first sight.
1) Exactly, the plan is to preserve the context for a given user to be able to
e.g. resolve co-references. How? Well, I am waiting for the GSoC proposals ;)
2) Adaptive basically means that it is about the backend not abound the
platform it is delivered to. The same backend should be usable for e.g. Slack,
Twitter, Facebook and the DBpedia Website at the same time.
Best regards
Ricardo
> On 17 Mar 2017, at 15:22, Rricha Jalota <[email protected]> wrote:
>
> 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
> <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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--
Ricardo Usbeck, M.Sc.
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