Web news site Digg is trying to make it easier for you to find stories that you would like to read. How will it do that? The same way Netflix (NFLX) tells you which movie you should rent: By finding users who have liked the same stories you have in the past, and then telling you what they’re digging right now.
The service is called Digg Recommendation Engine, and it’s a good idea: According to Digg, 16,000 stories are submitted to the site every day — and, beyond looking at the front page, it’s hard to sift through them.
When a user is looking through the “upcoming” section of new stories, the Recommendation Engine lets you know which like-minded users have dugg that story. You can also see a list of “Diggers like you,” which could lead you to interesting stories.
It’s a great feature for hardcore Digg users, who have recommended tens or hundreds of stories, but if you’re a casual user without much of a track record on the site, the service is probably not going to be much use to you right away. Anton Kast, Digg’s lead scientist, described the service in a video on the Digg blog:
“With 0 diggs, we have no information about you, we cannot produce a customised display, with one digg we can get started, but 10 or 100 is that much more.”
His point: Digg a bunch of stuff first! The feature launches this week in beta.
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