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Rachel Metz

A View from Rachel Metz

Diffbot Teaches Computers to Get Their Shop On

Diffbot’s latest API release could help shopping sites keep tabs on competitors’ prices.

  • July 31, 2013

Startup Diffbot, which uses machine-learning algorithms to tech computers to “understand” Web pages (see “A Startup Hopes to Help Computers Understand Web Pages”), has expanded its capabilities to the realm of online retail–a move that could make it easier to keep an eye on changing product prices and to display shopping website content on a variety of gadgets.

The company offers several application programming interfaces (APIs) that allow computers to “read” the different components of Web pages. An API for article pages, for example, can take a URL from a news website and pick out features like headlines, text, pictures, and tags. Similarly, the product API looks at a page, extracts data such as images, a product description, and the price, Diffbot CEO and cofounder Mike Tung says.

The release of this API in particular was important because of the popularity of online shopping, Tung says. He can imagine retailers using the API to more simply scour the Web to watch competitors’ changing prices, or sites like Pinterest to grab more detailed information from the product pages that users share with others.

It’s also the latest step in Diffbot’s plan to develop computer vision techniques that can analyze all of the many different types of Web pages out there–something the company thinks is necessary as we increasingly access the Web on multiple gadgets with different size screens, rather than just on desktop and laptop computers.

“The future is in having information in these structured databases, and being able to display it however you want as you move from your cellphone to your tablet to your Google Glass to your HD TV, for example,” Tung says.

You can try out a test of the product API, or any of the others the company offers, here.

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