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The Discovery tools include a powerful query interface that we can explore right in the browser. We'll use these tools to explore the AirBnb data we just added.
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Ben, what a great opportunity for
0:00
us to now query the Airbnb
documents that we put in.
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And I'm noticing right
there that there are 7%
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of negative sentiment happened with all
of the documents that we have uploaded.
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Let's explore that further.
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>> That sounds good.
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So I'm gonna go back into
the query editor, and
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we're gonna pick our reviews again,
get started.
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And yeah, you were saying that we can
use some natural language here and
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search for sentiments themselves,
like negative or bad.
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>> Absolutely.
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>> So yeah, let's just see what
happens if we search for bad.
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Certainly, a negative sentiment.
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>> Let's try the JSON.
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>> Okay, yeah, it looks like
we got one matching document.
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>> We got one matching document.
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>> And it certainly is a negative review.
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I can see a very bad experience,
impossible to sleep, etc, right.
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Okay, but they were seven percent.
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So what I found when I was
playing around with this,
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I'm gonna go back to the data set
itself because we can drill in here and
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we can view these things in the schema and
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that allows us to understand how
to query it a little bit better.
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>> Excellent.
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>> So if we click view in schema, we can
see that it brings out the sentiment and
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it has a bunch of different example
values, positive and negative.
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And if we scroll through,
we can see a bunch of different values And
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that means we can query
this string right here,
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enriched_text.sentiment.document.score.
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So if we go into the query-
>> Or maybe even the label.
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>> Right, the label, it would be great.
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We could choose positive-
>> Or negative, yes.
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>> Negative, or neutral, right.
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So let's hop back in, and this time we
wanna use the discovery query language,
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and as I use this more I
see how powerful it can be.
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So I'm gonna start typing because
it will auto complete for me.
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I wanted one of the sentiments, and like
you mentioned, you want to use the label.
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And if we select the is operator,
we can search for a specific one and
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it will prefill the ones that it detected.
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So we wanna see what
the negative ones look like.
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And if we run this we should see
the seven percent of documents.
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>> Fantastic.
>> So yeah, look at that 7 out of 101.
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So there's our seven percent.
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And it highlights in the results,
it drills down for us.
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You can see this matches the query syntax
enriched_text.entities.sentiment.label.
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And we can see the score that it got.
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>> Yes.
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>> And in the description we can
see what things were positive and
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what things were negative.
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>> Yes, yes.
>> And
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some of that may be in the review itself.
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Some of it may be in other
things that users comment on.
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>> Absolutely.
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>> Cool, so this is,
again, a powerful tool.
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It's very interesting to take a look and
work in it here and the web.
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But I want to see how to do this
with our chat bot again, right.
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How do we flip from our conversation
over to the discovery service itself?
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So let's take a short break and
then we'll check that out.
2:51
>> Wonderful, thank you, Ben, yes.
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