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So let's start with describing this task in a little bit more detail.
Okay, so let's say we're sitting here, reading an article.
Here we are, reading our article.
And actually it's Carlos who's reading this article,
because this is an article about soccer.
Or as he would call it football if he was wearing his Argentina jersey
or footsie ball if he was wearing his Brazil jersey and
clearly, I'm not pronouncing either of those words correctly.
Carlos can correct me later.
But the point is that he likes this article and what we'd like
to do is retrieve another article that he might be interested in reading.
But a question is how do we do this?
There are lots and lots of articles out there and I can't expect him to go and
read each of them and say yes, he's interested or no, he's not.
So we like to think of a way to automatically retrieve a document that
might be of interest to him.
By questions here are first, how to we measure similarity between articles?
We need to have that in order to say that this article is similar to the one he's
reading now and might also be of interest to him.
Or that, here's a large set of articles that are very different and
probably are not of interest to him.
And then the second question is, how are we gonna search over the articles that
exist out there and retrieve the next article to recommend.
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