Evri Teams Up with The Times of London, Helps Online Audience Browse the Web Better

Seattle-based Internet startup Evri is announcing today that it has formed a partnership with The Times of London, one of the UK’s leading newspapers, to provide content recommendation software for online articles. For selected stories in the Times Online, Evri’s widget shows up next to the text with a list of links to related articles from the paper’s archives (and some outside websites). The news comes on the heels of a similar deal with the Washington Post that Evri announced last month.

It’s all part of Evri’s continuing efforts to build its audience, says Neil Roseman, the company’s founder and chief executive. Evri was started in 2007, and is backed by $8 million from Paul Allen’s Vulcan Capital. The concept is to use natural language processing to understand connections between entities on the Web—people, products, things—and help you browse what you’re interested in more efficiently. While it’s not intended to replace search engines, Evri does want to change fundamentally how people browse the Web. (Roseman recently wrote about presenting some new features at DEMO 09.)

Financial terms of the Times Online partnership weren’t disclosed, but it is important for several reasons. One, it is a “very significant traffic source,” says Roseman, who points to the site’s 20 million-plus monthly users. Two, it “reinforces our focus on English language articles, not just American journalism,” he says. And three, it “helps further prove the model.”

That model says people will appreciate being directed to other content on the Web that is related to what they’re reading about, not just because it contains some of the same keywords, but because the underlying meaning of sentences in the articles is related. Roseman gives the simple example of Evri’s software being able to tell the difference between Michael Jackson, the pop singer, and Michael Jackson, an actor, from an article’s context.

But one of the technical challenges is how to understand meanings and relationships reliably in everything from a 140-character message on Twitter to a full article in The Economist, say. “That hadn’t been done before with natural language processing,” Roseman says. “The technology is definitely getting better.”

Roseman, a former vice president of technology at Amazon, says he has learned … Next Page »

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