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One of the hottest frontiers in Web search is finding ways to improve results based on the searchers’ preferences. Already, when you log in to Google, the search engine tries to personalize results by mining your search history: for an eighth grader who has performed lots of searches on marine life, a search for “dolphins” might provide more results for the animal than for the football team.

Now Surf Canyon, a startup based in Oakland, CA, is adding its own spin on personalization. Its software, which can be downloaded and installed into Firefox and Internet Explorer Web browsers, enhances individual searches on major search engines by evaluating which links you click on, and then instantly giving you revised search returns–including three sites that relate in some way to the site you clicked on. “We have invented real-time personalization,” says Mark Cramer, CEO of the company.

For example, a Google search for “thermoelectric cooler” using Firefox with Surf Canyon installed provides 10 standard results. In my case, the eighth result, from freescale.com, a chip maker, seemed promising. I clicked on it, scanned the page, and then hit the “back” button. When I subsequently looked at the results page, three new suggestions appeared directly under the freescale.com result. Surf Canyon had elevated these links from the earlier 100 pages of results because its algorithm determined that these recommendations related to the information on freescale.com, including technical explanations of how thermoelectric coolers work.

Crucially, these new results are cleverly slipped into the search results so that the original results page doesn’t look drastically different when a user navigates back. It would be off-putting to users, Cramer says, if they had seen a link in the original results that they wanted to click on but, when they went back to the results, found it missing. Therefore, recommended results only appear automatically below the link that was clicked on. “We don’t want to jar the users,” Cramer says. “[Surf Canyon is] specifically engineered to be as unobtrusive as possible.”

Behind the scenes, an algorithm makes the personalization possible. Among other things, the algorithm analyzes which results are clicked, which are ignored, and how much time a user spends looking at the page. Importantly, says Cramer, the algorithm semantically deconstructs a page to determine what it means and how similar it is to others in the results. The results are cumulative: after a couple of clicks, the algorithm can determine if you’re most interested in a Canon camera, an SLR camera, or, specifically, a Canon SLR, Cramer says.

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Credits: Technology Review, Kate Greene

Tagged: Communications, Web, Google, search, personalization

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