To show how deep learning may work in practical settings, we will explore product matching.
Up-to-date pricing is very important for large internet retailers. In situations where your competitor lowers the price of a popular product, late reaction leads to large profit losses. If you know the correct market price distributions for your product catalog, you can always remain a step ahead of your competitors. To create such a distribution for a single product, you first need to find this product description on a competitor's site. While automated collection of product descriptions is easy, product matching is the hard part.
Once we have a large volume of unstructured text, we need to extract product attributes from it. To do this, we first need to tell whether two descriptions refer to the same product. Suppose that we have collected a large dataset of...
