Digg Recommendation Engine from Kevin Rose on Vimeo.

Anton Talks About The Digg Recommendation Engine from Kevin Rose on Vimeo.

Not all the users have these features enabled yet, but those of you who do can check by going to upcoming and checking for a red BETA label. The new upcoming system has three ways to sort it and the third option in the list, Most Diggs, is the one you're used to seeing, where all stories are presented in order of decreasing Diggs.

The first new option, Most Matches, looks at your history of Digging, compares it with other community members, and shows the stories in order of number of matches. In the case of the first story, you see the expanded view of the 'Recommendations via' list, and in the case of the second story, you see it in the compact version, not showing the user names and percentages, rather only the total number. For example:

The second new option, Most Recent, shows you the stories recommended by community members compatible with you, in reverse chronological order. You can also see why a story was recommended to you (via user name and percentage of compatibility with that user).

A new section in the sidebar, entitled 'Diggers Like You' shows you Diggers that are most like you in their Digging and submitting habits.

And finally, you can click on a user and compare exactly how much you overlap. In the screenshot you see below you can see the overlap between my profile and thediggboss's profile. In total we had 3864 overlapping Diggs in the past 30 days, which means our compatibility score over all our Digg activity is 38%.

Overall the design is great and there is a decent feature set. As far as what it is designed to do, it seems to function well. At the same time however, whether the engine will help content submitted by a fairly obscure user, remains to be seen. In the beginning, all your compatibilities are going to be with the people that you have been Digging and the people that have been Digging you back, i.e. your friends. It will require widespread use of the feature 'Diggers Like You' to help more obscure submissions travel to a lot of people.

It is also important to note that the recommendation engine will be a boon to advertisers as well (and of course Digg). By sending the most relevant links to the most relevant people, you can also send the most relevant advertisements to the right people (and ensure high-quality clickthroughs). Users get good content and related, hopefully non-intrusive ads, advertisers get the right potential customers, and Digg gets the money.

This is a guest post by Muhammad Saleem, a social media consultant and a top-ranked community member on multiple social news sites. You can follow Muhammad on Twitter.

Special thanks to thediggboss for providing the images.