Microsoft's Bing Matchbox technology promises a new form of personalized search. The search engine tests it with Project Emporia apps for the Web and Windows Phone 7 smartphones.
Microsoft's Bing search engine is testing a new
technology aimed at tailoring search results to individual user's tastes, two
experimental applications that recommends news stories shared on Twitter.
What Google describes as personalization Bing is calling
Matchbox, which attempts to make predictions about what searchers might want to
see, based on if someone like them has done something with it but also on what
the content says.
Traditional personalization technologies from Google use
collaborative filtering, which means if user A and user B both like something,
the search engine can predict user A's future "likes" based on what
user B "likes." It's a sort of taste by association, or in Bing's parlance,
collaboration.
Ralf Herbrich, principal development manager for Bing
Mobile Personalization,
noted that this approach works well for static products, as well as restaurants
and movies. However, it does little to help account for evolving news and
real-time information.
Herbrich's cites the example of a user reading and rating
articles on electric cars. Collaborative filtering techniques would look at
other people who have read similar articles and cluster the searcher with them.
New articles related to electric cars may be recommended to a user provided a
user with similar tastes interacts with it.
But that is a hit and miss value proposition because, as
Herbrich noted, it doesn't help the first person searching for fresh content on
electric cars find the article.
Matchbox uses the information about the entities
mentioned in an article. So because Matchbox knows that Tesla is an electric
car, it can retrieve "Tesla Model S: 300 miles on 1 charge" as a
viable search result with relying on input from other people who conducted
similar searches.
The idea of this "feature generalization" is to
grok the Web more like a human than a machine. In short, it's applying
artificial intelligence to search.
To test Matchbox in a practical scenario, Bing built
Project Emporia a new Web application and Windows Phone 7 app users can test.
Emporia, which Bing demonstrated at South By Southwest
Interactive over the weekend, recommends news stories shared on Twitter using
the Matchbox technology.
The apps filter news stories by automatically predicted
news categories. Integration with Twitter helps users see what stories your
friends and friends-of-friends are sharing. Finally, the apps recommend news
stories based on searchers' personal preference votes.
"This new approach will help users getting on top of
the wealth of news coming at them every day," Herbrich said.
Perhaps, but the technology in its infancy appears
limited to social search. Will the technology remain relegated to Web and
mobile apps, or make its way into the broader Bing search engine as a regular
feature?
More importantly, will it improve Bing's relevance, which
is already solid, enough to help the search upstart
further nip at Google's search share?
And how will Matchbox fit into the Bing
personalized search Microsoft
introduced last month? When a user searches in Bing for the same search term on
multiple occasions, and clicks on a link presented further down on the results
page, the search engine will start bringing that link to the top of the page.
Google isn't standing still on this front. The company is
building new search results based on contextual discovery, or leveraging users'
locations and personal preferences to deliver custom results.
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