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There are many systems for restaurant reviews out there but
today we're gonna talk about a pretty new and exciting one that we can build.
So it's an important day for
us and we're trying to book a Japanese restaurant, and
we love Japanese food and want a really cool place to have some Japanese food.
But this is Seattle that we live in, and Seattle is really awesome for
Japanese food, so there are many, many places for sushi, and in fact,
there are many that have really good ratings, say four stars.
So perhaps when I'm thinking about a restaurant to go to
I'm not just thinking about the overall stars of the restaurant, but
I'm thinking about how is it in terms of the food, in terms of the ambiance?
In particular how is it in terms of the sushi,
which is the thing that I really care about.
I really love sushi and I want really, really the best, freshest fish,
and the most awesome, innovative sushi I can get.
So when you talk about a positive review for a restaurant, and here's a restaurant
that we love in Seattle, a sample review might go something like this.
So watching the chefs create an incredible,
edible piece of art, was really a unique experience.
So the experience is really positive if we think about that aspect of the restaurant.
But a review might want to say, well, my wife tried the ramen, and
it was pretty forgettable.
That means the ramen, not so good.
Now, the review continues and says,
all the sushi was delicious, easily the best sushi in Seattle.
So the sushi was really two thumbs up.
Now, I don't care about the ramen.
I'm not going to this place for ramen.
I don't care that this person really didn't like the ramen,
or his wife really didn't like the ramen.
What I really care about is good experience and amazing sushi.
So this review is just for me.
So when I'm thinking about restaurant reviews,
I wanna understand the aspects of the restaurant, their positive or
negative, and really think about which ones of those really affect my interests.
So if I look at all the restaurant reviews, I want to feed them to this new,
really exciting, new type of restaurant recommendation system that's gonna tell me
the experience was good, four stars.
The ramen was a so-so, but who cares?
But the sushi, the thing that I really care about, that was five stars, and
not just that, it's gonna give me some interesting feedback, so for
example, this is easily the best sushi in Seattle.
Now that's where I wanna go.
So how do we build such an intelligent restaurant review system?
Well we're going to start with all the reviews and
we're going to break them up into sentences.
So each review is composed of multiple sentences and
some sentences cover different aspects of the restaurant.
So for example, a sentence that says easily the best sushi in Seattle,
I wanna feed that sentence through a sentiment classifier.
So sentiment classifier is gonna say is this sentence positive, or
is it a negative sentence?
Now we have a sentiment classifier, which can take a sentence and
say is it positive or negative?
So how do we build this new kind of cool restaurant review experience?
So we're gonna take all the reviews and
break them into sentences that will be discussed but
then we're gonna select the sentences that talk about the aspect I care about.
So which ones of these are really about sushi?
So not all of them, but a subset of those.
Then I feed those sentences through the sentiment classifier,
each one of them, and then I average the results.
In this case all of the sentences were positive and
so I'm gonna say this is a five star restaurant review in terms of the sushi.
Not just that, I can look at the sentences about sushi and
look at which ones are most positive.
So for example, this one must be the positive, but easily the best
restaurant in Seattle maybe is the most positive, and I can display those.
I can also display the most negative ones.
In this case, there's nothing negative to say about the sushi.
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