At SXSW Interactive in Austin, TX, Microsoft showcased a new approach to personalization. Rather than looking only at what others like you're interacting with on the web, the Matchbox technology begins to "understand" the Web more like a human might. This enables us to make predictions about what you might want to see, not only based on if someone like you has done something with it but also on what the content says.
Project Emporia is the first broad implementation of the Matchbox technology that you can use. Project Emporia is a new web app and a Windows Phone 7 app that recommends news stories shared on Twitter using the Matchbox technology. It combines three major pieces of technology:
- Filter news stories by automatically predicted news categories
- Deep social integration of Twitter so you can see what stories your friends and friends-of-friends are sharing as well as curate your Twitter network
- Recommend news stories based on your personal preference votes
"For e.g.: let's say over the past several weeks you have been reading and rating articles on electric cars. Traditional collaborative filtering techniques would look at other people who've read similar articles and cluster you with them. So when a new article comes out about Tesla's new model, as long as someone "like you" interacts with it, it might get recommended to you. But how does that first "someone like you" find it in the first place? That's where Matchbox can help.
Rather than simply relying on the actions of others, the Matchbox technology uses the wealth of information about the entities mentioned in an article. In this case, Matchbox knows that Tesla is an "electric car". With this additional info, it can display "Tesla Model S: 300 miles on 1 charge" to you without having to receive input from other like-minded individuals. For those geeking out, this technique is called "feature generalization" and is a key underpinning of Matchbox," explains Microsoft.